{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "Good AI Labs — Open roles",
  "home_page_url": "https://www.goodailabs.com/careers/",
  "feed_url": "https://www.goodailabs.com/careers/feed.json",
  "language": "en",
  "items": [
    {
      "id": "https://www.goodailabs.com/careers/research-scientist-world-models/",
      "url": "https://www.goodailabs.com/careers/research-scientist-world-models/",
      "title": "Research Scientist, Foundation Models",
      "summary": "Develop foundational models for robotics, from pretraining and multimodal learning to adaptation through interaction.",
      "content_html": "<p>Good AI Labs is developing foundational models for robots that can learn new tasks and act in unfamiliar environments. We are hiring a Research Scientist to advance the capabilities of these models through new architectures, training methods and learning signals.</p><p>You will own a research direction from the idea to the trained model. The scope includes multimodal pretraining, representation learning, adaptation and the use of simulation and reinforcement learning. This is a role for someone who has trained models, understands why a run succeeds or fails, and has a considered view on what the next generation of embodied intelligence should learn.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop and train foundational models that connect visual observations, language and physical interaction.</li><li>Investigate pretraining objectives, data mixtures and model architectures that improve transfer across tasks and environments.</li><li>Design training experiments that separate the effects of model capacity, data quality, optimisation and compute allocation.</li><li>Explore how simulation, demonstrations and reinforcement learning can extend capabilities beyond pretraining.</li><li>Own the experimental work: implement the method, diagnose training behaviour, run ablations and establish where the improvement holds.</li><li>Work with research and systems engineers on training efficiency, inference constraints and the path from a research result to robot behaviour.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>BS, MS or PhD in computer science, machine learning, mathematics or a related field, or demonstrated research and engineering work of equivalent depth.</li><li>Original contributions to foundation models or multimodal learning, with direct responsibility for model implementation, training and evaluation.</li><li>A strong research record demonstrated by first-author or leading contributions at venues such as NeurIPS, ICML, ICLR, CVPR or CoRL, or substantial industrial or independent research with comparable originality and technical depth.</li><li>Hands-on experience training deep-learning models: preparing data, choosing objectives and optimisers, managing checkpoints and resolving instability or poor generalisation.</li><li>Strong Python and PyTorch skills, with the ability to implement research ideas beyond an existing training recipe.</li><li>The judgement to identify an important open problem, test competing explanations and decide which result warrants further investment.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Multimodal foundation models, generative modelling, video learning or representation learning from sequential data.</li><li>Distributed training, mixed precision, training-data curation or analysis of scaling behaviour.</li><li>Reinforcement learning, simulated environments or transfer from pretrained representations to physical tasks.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Send your CV and two or three contributions that best represent your research. For one model you trained, describe the problem, your own implementation work, the training setup and the result. Papers, code, technical reports and accounts of substantial proprietary work are all relevant. Tell us which research question you would want to own here.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Foundation+Models\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Foundation model training",
        "Multimodal learning",
        "Embodied intelligence"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Foundation+Models"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-scientist-world-action-models/",
      "url": "https://www.goodailabs.com/careers/research-scientist-world-action-models/",
      "title": "Research Scientist, Reinforcement Learning",
      "summary": "Advance how foundational models learn through interaction, with reinforcement learning and simulation for robotics.",
      "content_html": "<p>We are hiring a Research Scientist to develop reinforcement-learning methods for embodied intelligence. The objective is to help foundational models acquire new capabilities through interaction, improve with feedback and adapt their behaviour when a task changes.</p><p>You will work across the learning algorithm, reward signal, training environment and resulting policy. Simulation is central to this role: it provides a way to study exploration, scale experience collection and test behaviour before physical evaluation. We are looking for someone who can turn an open research question into a training system and explain what the learned policy is actually doing.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop reinforcement-learning algorithms and training objectives for policies that must learn from demonstrations, feedback and interaction.</li><li>Investigate reward design, exploration, credit assignment and curricula for tasks that require sustained sequences of actions.</li><li>Build experiments that connect pretrained foundational models to policy learning and adaptation.</li><li>Use simulation to study sample efficiency, robustness and transfer, including the effects of environment design and training distributions.</li><li>Diagnose training instability, reward exploitation and policy failures through targeted experiments and trajectory analysis.</li><li>Collaborate with robotics and systems engineers on experience collection, distributed training and evaluation on physical tasks.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>BS, MS or PhD in machine learning, robotics, computer science or a related quantitative field, or demonstrated work of equivalent technical depth.</li><li>Original reinforcement-learning research or substantial learning systems, with hands-on responsibility for training policies and evaluating their behaviour.</li><li>A research record demonstrated by leading contributions at venues such as NeurIPS, ICML, ICLR, CoRL or RSS, or research systems that establish comparable algorithmic and experimental depth.</li><li>Practical experience implementing RL algorithms, managing rollout collection and debugging optimisation, rewards and environment behaviour.</li><li>Strong Python and PyTorch skills, supported by a sound understanding of probability, optimisation and sequential decision-making.</li><li>The ability to design controlled evaluations and distinguish a policy improvement from an easier environment, altered reward or change in available data.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Offline or online RL, imitation learning, policy optimisation or learning from human feedback.</li><li>Physics simulation, manipulation, domain randomisation or transfer between simulated and physical systems.</li><li>Distributed rollout systems, curriculum learning or adaptation of pretrained models through reinforcement learning.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and selected research or engineering contributions. Describe an RL training project you personally developed: the environment, learning signal, policy, principal failure modes and final result. Include code, publications or rollout demonstrations where available, and explain the next problem you would want to investigate.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Reinforcement+Learning\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Reinforcement learning",
        "Policy training",
        "Simulation"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Reinforcement+Learning"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-scientist-robot-learning/",
      "url": "https://www.goodailabs.com/careers/research-scientist-robot-learning/",
      "title": "Research Scientist, Robot Learning",
      "summary": "Train policies that turn foundational-model capabilities into robot skills, with a focus on manipulation, adaptation and transfer.",
      "content_html": "<p>Good AI Labs is hiring a Research Scientist to advance learning for robotic manipulation. You will develop policies that acquire skills from demonstrations and interaction, then investigate how those skills transfer to new objects, task variations and operating conditions.</p><p>The work connects foundational models with imitation learning, reinforcement learning and simulation. You will own the training and evaluation of a research direction, working with engineers to understand how a policy behaves when it controls a robot. We are interested in researchers who can move between a new learning idea and the practical details that determine whether it works.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Design and train policies that use visual observations, task context and interaction history to perform manipulation tasks.</li><li>Develop imitation-learning and reinforcement-learning methods that improve skill acquisition, adaptation and recovery.</li><li>Investigate how demonstration quality, data mixtures and action representations affect learning and generalisation.</li><li>Build simulation experiments and evaluation protocols that test task transfer and expose gaps before physical deployment.</li><li>Work with robotics engineers to analyse failed rollouts, sensing delays, action timing and differences between simulation and hardware.</li><li>Establish the relationship between task performance, training data and inference requirements, and use it to guide further model development.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>BS, MS or PhD in robotics, machine learning or a related discipline, or demonstrated research and robotics work of equivalent depth.</li><li>A strong record in robot learning, with direct experience implementing, training and evaluating policies for embodied tasks.</li><li>Original contributions demonstrated through publications at venues such as CoRL, RSS, ICRA, IROS, NeurIPS or ICML, or substantial robot-learning systems with comparable technical merit.</li><li>Strong Python and deep-learning implementation skills, including the ability to diagnose training failures from data, model behaviour and rollouts.</li><li>A working command of robot observations, action spaces, control frequency and closed-loop evaluation.</li><li>Evidence that you can lead a research project through implementation, experimentation and a result that holds beyond its easiest test cases.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Foundational models for robotics, multimodal policies, multi-task learning or learning from heterogeneous demonstrations.</li><li>Simulation, reinforcement learning, domain randomisation or sim-to-real transfer.</li><li>Physical manipulation experiments, data collection or adapting policies across robot embodiments.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and selected papers, code or demonstrations. Describe a policy you trained, the data and environment it used, your contribution and the conditions under which it succeeded or failed. We welcome both academic research and substantial engineering work on learning-based robots.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Robot+Learning\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Robot policy training",
        "Manipulation",
        "Sim-to-real transfer"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Robot+Learning"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-scientist-computer-vision/",
      "url": "https://www.goodailabs.com/careers/research-scientist-computer-vision/",
      "title": "Research Scientist, Computer Vision",
      "summary": "Train visual models that give robots useful representations of objects, motion and physical interaction.",
      "content_html": "<p>We are hiring a Research Scientist to develop visual learning for embodied intelligence. You will investigate how foundational models can learn representations of objects, motion and interaction that remain useful as a robot moves through a changing environment.</p><p>This role combines model research with practical training experience. The questions include what visual pretraining should capture, how temporal information should be represented and which learning signals produce useful transfer to physical tasks. You will shape a research direction and work with robotics researchers to evaluate the capabilities it enables.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop and train visual models using images, video and observations from embodied tasks.</li><li>Investigate representation learning and pretraining objectives for objects, motion, geometry and interaction.</li><li>Study temporal information, partial visibility and changing viewpoints, with evaluations that test generalisation to unfamiliar scenes.</li><li>Design data-selection and training experiments that isolate the causes of improved visual understanding.</li><li>Connect visual evaluation to downstream policy performance, including the consequences of uncertainty and perceptual errors.</li><li>Collaborate on efficient training and inference so promising visual capabilities can be used within a robot’s resource constraints.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>BS, MS or PhD in computer vision, machine learning, computer science or a related field, or demonstrated work of equivalent technical depth.</li><li>Original work in computer vision, supported by hands-on experience training visual models and evaluating generalisation.</li><li>A strong research record through first-author or leading work at venues such as CVPR, ICCV, ECCV, NeurIPS or ICLR, or substantial industrial or independent research of comparable depth.</li><li>Practical knowledge of visual-data pipelines, augmentation, training objectives and optimisation, including debugging model collapse, overfitting or poor transfer.</li><li>Strong Python and PyTorch skills, and sound foundations in geometry, linear algebra and statistical learning.</li><li>The ability to identify a consequential visual-learning problem and carry it through a convincing implementation and evaluation.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Multimodal foundation models, self-supervised learning, video representation learning or embodied perception.</li><li>Simulation and synthetic data for training visual models and testing robustness.</li><li>Vision for manipulation, visual feedback in policy learning or inference under limited compute.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and selected research contributions. For one visual model you trained, explain the data, learning objective, implementation work and evaluation. Papers, code, visual demonstrations and substantial proprietary projects can all establish the quality of your work.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Computer+Vision\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Visual pretraining",
        "Video understanding",
        "Embodied perception"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Computer+Vision"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-scientist-computational-neuroscience/",
      "url": "https://www.goodailabs.com/careers/research-scientist-computational-neuroscience/",
      "title": "Research Scientist, Computational Neuroscience",
      "summary": "Develop computational approaches to learning, memory and adaptation that can improve embodied intelligence.",
      "content_html": "<p>Good AI Labs is hiring a Research Scientist in Computational Neuroscience to investigate mechanisms that help artificial systems learn, retain useful experience and adapt. We are interested in scientific ideas that can lead to more capable foundational models and robots that continue learning as they interact with the world.</p><p>You will develop computational hypotheses, implement and train models, and test their behaviour in controlled environments. Simulation and reinforcement learning provide practical settings for studying skill acquisition, memory and adaptation. The role calls for depth in the science and the ability to turn that understanding into a working learning system.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop computational accounts of learning, memory, credit assignment or adaptation with a clear experimental formulation.</li><li>Implement and train models that test how a proposed mechanism affects acquisition, retention, interference and transfer.</li><li>Design simulated tasks and behavioural experiments that distinguish competing explanations.</li><li>Work with machine-learning researchers to incorporate useful mechanisms into continual-learning and reinforcement-learning systems.</li><li>Compare methods under controlled experience and compute budgets, examining behaviour across repeated learning rather than a single task.</li><li>Connect the findings to the neuroscience literature and identify which conclusions can inform further robotics research.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>BS, MS or PhD in computational neuroscience, cognitive science, machine learning, applied mathematics or a related field, or demonstrated research of equivalent depth.</li><li>Original computational research on learning, memory or adaptive behaviour, with experience implementing and training models.</li><li>A research record demonstrated by leading contributions in neuroscience, cognitive science or machine learning, or computational systems and technical work of comparable scientific depth.</li><li>Strong mathematical modelling and statistical inference, including the ability to compare models and identify what an experiment can establish.</li><li>Proficiency in Python and experience with numerical methods or deep-learning frameworks for model training and analysis.</li><li>The ability to work across scientific disciplines and defend a proposed learning mechanism with both theoretical reasoning and experimental results.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Continual learning, memory consolidation, credit assignment, sensorimotor learning or adaptive behaviour.</li><li>Reinforcement learning, recurrent models or simulated environments for studying learning over time.</li><li>Connecting computational theory to behavioural evidence or transferring a scientific hypothesis into an implemented learning method.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and two or three research contributions. Explain your role in one computational model, how it was trained or fitted, and which evidence supports its account of learning. We are interested in the depth of the work whether it came from a degree programme, an industrial lab or independent research.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Computational+Neuroscience\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Learning and memory",
        "Continual learning",
        "Computational modelling"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Scientist%2C+Computational+Neuroscience"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-engineer-embodied-ai/",
      "url": "https://www.goodailabs.com/careers/research-engineer-embodied-ai/",
      "title": "Research Engineer, Simulation & Reinforcement Learning",
      "summary": "Build simulation environments and train policies that improve through interaction, with a clear path to physical robots.",
      "content_html": "<p>Good AI Labs is developing foundational models for robots that learn through experience. We are hiring a Research Engineer to build the simulation and reinforcement-learning systems that make this research possible. You will develop environments, train policies and investigate whether improvements survive changes in the task and the physical system.</p><p>Simulation is part of the learning process, not just a place to run a demonstration. You will work across physics, task design, rollout collection and model training. The role calls for someone who can debug both a simulator and a learning algorithm, and recognise when a policy has exploited a flaw in the environment rather than learned the intended behaviour.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Build simulation environments for robot interaction, including observations, actions, contacts, reset logic and task termination.</li><li>Implement and train RL policies; develop rewards, curricula and evaluation conditions that capture the intended task.</li><li>Connect simulated experience to foundational-model training and adaptation, working with researchers on learning objectives and data collection.</li><li>Build parallel rollout, replay and evaluation systems; profile the balance between simulation throughput, training compute and data transfer.</li><li>Investigate sim-to-real transfer through appropriate variation in dynamics, sensing and task conditions, then compare against physical observations.</li><li>Diagnose reward exploitation, unstable training and simulator artefacts; maintain reproducible baselines, held-out tasks and failure analysis.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>BS, MS or PhD in computer science, robotics, engineering or a related field, or demonstrated technical work of equivalent depth.</li><li>Hands-on experience implementing and training reinforcement-learning policies, with responsibility for the environment, learning loop and evaluation.</li><li>Strong Python and PyTorch skills, with the ability to implement methods from papers and inspect the training code beneath a framework.</li><li>Practical understanding of policy optimisation, exploration, reward design and the effect of observation and action spaces on learning.</li><li>Experience building or modifying physics-based environments and debugging issues involving dynamics, contacts, coordinate frames or timing.</li><li>A record of substantial engineering work that other people can run, inspect and extend, supported by clear experiments and sound software design.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Robot manipulation, locomotion, imitation learning, offline RL or adaptation of pretrained models through interaction.</li><li>Physics engines such as MuJoCo or Isaac, GPU simulation, parallel environment execution or distributed rollout collection.</li><li>Domain randomisation, system identification, hardware-in-the-loop testing or deploying learned policies on physical robots.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and a simulation or RL project you built. Describe the environment, training method, compute setup and evaluation. Explain a failure you diagnosed and what changed after your intervention. Code, training curves, rollout videos and technical reports are useful; clearly identify your own contribution.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Engineer%2C+Simulation+%26+Reinforcement+Learning\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Physics simulation",
        "RL policy training",
        "Sim-to-real transfer"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Engineer%2C+Simulation+%26+Reinforcement+Learning"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/ml-systems-engineer/",
      "url": "https://www.goodailabs.com/careers/ml-systems-engineer/",
      "title": "ML Systems Engineer, Training & Inference",
      "summary": "Make training dependable and inference fast enough for robotics, from data loading to execution on CPU and GPU.",
      "content_html": "<p>We are hiring an ML Systems Engineer to improve the training and execution of models for robotics. You will work on the systems behind foundational-model training, reinforcement learning and computer vision, with responsibility for performance, reliability and efficient use of compute.</p><p>The work requires understanding the full path from data preparation to model execution. A useful improvement may come from a training pipeline, memory layout, inference runtime or the way observations reach the model. You will identify the bottlenecks that matter, implement changes and verify their effect under the conditions in which researchers and robots use the system.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Profile training and inference workloads to locate bottlenecks in computation, memory, data loading and device communication.</li><li>Improve CPU and GPU execution through appropriate changes to batching, precision, compilation, memory use or runtime configuration.</li><li>Build reliable training infrastructure for distributed execution, checkpointing, recovery and tracking resource use.</li><li>Support simulation and RL workloads where rollout collection, policy updates and evaluation compete for compute.</li><li>Develop performance benchmarks that capture throughput, latency distributions, peak memory and numerical behaviour under documented conditions.</li><li>Work with researchers to make new architectures trainable and to understand the systems implications of model and data choices.</li><li>Support integration of inference into robotics workflows, accounting for input preparation, data transfer and the time available to produce an action.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li><p>BS, MS or PhD in computer science, computer engineering or a related field, or substantial systems work demonstrating equivalent technical depth.</p></li><li><p>Direct experience building or operating model-training systems, with ownership of performance, reliability or distributed execution.</p></li><li><p>Proficiency in Python and a deep-learning framework such as PyTorch, with the ability to investigate behaviour below the model API.</p></li><li><p>Solid understanding of memory hierarchies, concurrency and CPU or GPU execution, supported by practical profiling experience.</p></li><li><p>Experience diagnosing numerical, performance or reliability problems and validating a fix against reproducible workloads.</p></li><li><p>Strong software engineering fundamentals, including testing, Linux systems and clear technical documentation.</p></li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Distributed training, data and model parallelism, accelerator programming, kernel optimisation or model compilation.</li><li>Training-framework internals, gradient synchronisation, dataloader stalls or numerical problems in mixed-precision training.</li><li>Quantisation, mixed-precision execution, inference runtimes or deployment on devices with limited memory and power.</li><li>Systems work involving real-time inputs, changing batch sizes or strict latency requirements.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and a systems project or performance investigation you led. Describe the workload, the original bottleneck and the improvement, with measurement conditions and any trade-offs. Code, profiler traces or a technical report can help explain the depth of your contribution.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+ML+Systems+Engineer%2C+Training+%26+Inference\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Distributed training",
        "GPU performance",
        "Inference systems"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+ML+Systems+Engineer%2C+Training+%26+Inference"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-engineer-agent-systems/",
      "url": "https://www.goodailabs.com/careers/research-engineer-agent-systems/",
      "title": "Research Engineer, Agent Systems",
      "summary": "Build persistent memory and dependable task execution for agents that work across tools, sessions and interruptions.",
      "content_html": "<p>We are looking for a Research Engineer to develop persistent agents for tasks that require memory, planning and recovery. You will build the software that lets an agent retain useful context, use tools and resume work when a task spans multiple sessions or encounters a failure.</p><p>These questions also matter for robots carrying out extended tasks: keeping track of progress, deciding what to do next and recovering from interruptions. You will advance the agent infrastructure and investigate how it can support task-level robotics workflows. The role combines stateful software engineering with empirical work on agent behaviour.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop durable task state, memory and execution mechanisms that preserve progress across interruptions and restarts.</li><li>Build tool integrations with clear inputs, permissions and results, including appropriate handling of timeouts and partial failures.</li><li>Design recovery and retry behaviour for concurrent work, with particular attention to preventing unintended repeated actions.</li><li>Build evaluations for task completion, memory use and recovery, and create traces that make failures understandable and reproducible.</li><li>Improve context management, execution latency and resource use without losing information needed for the task.</li><li>Work with robotics researchers to define and test interfaces between task-level agents, simulation environments and robot capabilities.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li><p>BS, MS or PhD in computer science, engineering or a related field, or demonstrated systems and research work of equivalent depth.</p></li><li><p>Strong software engineering experience with stateful services, asynchronous execution, workflow systems or agent infrastructure.</p></li><li><p>A solid understanding of concurrency, persistence and failure recovery, with examples of systems you have personally designed and debugged.</p></li><li><p>Practical experience integrating models, external APIs or execution tools into a working application.</p></li><li><p>The ability to analyse agent behaviour across prompts, model outputs, stored state and tool execution, and turn the analysis into a useful evaluation.</p></li><li><p>Careful judgement about permissions and side effects, along with strong testing and technical communication skills.</p></li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Persistent agents, memory systems, workflow engines or tools that execute code and interact with user environments.</li><li>Agent benchmarks, task verification, sandboxing or observability for complex software execution.</li><li>Task planning, human supervision or interfaces between software agents and physical systems.</li><li>Training or adapting agent models, reinforcement learning from interaction, or constructing tasks for behavioural evaluation.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and an agent or stateful system you have built. Explain the architecture, your contribution and a difficult failure you resolved. We are interested in how you evaluated reliability over repeated runs, as well as what the system could accomplish.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Research+Engineer%2C+Agent+Systems\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Agent memory",
        "Task execution",
        "Behavioural evaluation"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Research+Engineer%2C+Agent+Systems"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/robotics-engineer/",
      "url": "https://www.goodailabs.com/careers/robotics-engineer/",
      "title": "Robotics Engineer",
      "summary": "Bring sensing, control and learned policies together on physical robots, with responsibility for integration and testing.",
      "content_html": "<p>We are hiring a Robotics Engineer to connect our learning systems to physical robots. You will own the software and integration work between sensors, actuators, control interfaces and learned policies, and work directly with hardware to make experiments dependable.</p><p>This role sits between research and the machine. It requires an understanding of how a robot should behave and the practical ability to determine why it behaves differently. You will work with researchers, electronics engineers and mechanical engineers to bring systems into operation, improve their reliability and support increasingly demanding tasks.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop and maintain interfaces for robot sensors, actuators and policies, with consistent units, coordinate frames and timing.</li><li>Implement calibration and synchronisation procedures, and validate the observations and state estimates supplied to learning systems.</li><li>Integrate learned policies with robot controllers, accounting for execution frequency, delays, operating limits and interruption handling.</li><li>Build diagnostics, recording and replay tools that connect commanded actions to observed motion and sensor readings.</li><li>Build tests that connect simulation and physical experiments; investigate failures across subsystems and verify fixes through repeatable procedures.</li><li>Work with hardware and research teams on interface requirements, integration priorities and documentation for operating the robot.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li><p>BS, MS or PhD in robotics, computer science, electrical or mechanical engineering, or hands-on robotics work demonstrating equivalent technical depth.</p></li><li><p>Hands-on experience developing robotics software and bringing a robot or comparable electromechanical system into operation.</p></li><li><p>Strong programming skills in C++ and Python, with practical experience debugging on Linux.</p></li><li><p>A sound understanding of kinematics, coordinate transforms, feedback control and sensor calibration.</p></li><li><p>Experience diagnosing problems involving hardware, communication and software, using measurements to isolate their cause.</p></li><li><p>The ability to work closely with researchers and hardware engineers, make integration decisions and document the resulting system clearly.</p></li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Manipulation, robot middleware, motion interfaces or real-time communication.</li><li>Integrating policies trained with reinforcement or imitation learning into physical robots, simulation or hardware-in-the-loop tests.</li><li>Test automation, sensor synchronisation or development of tools for collecting robot experience.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and a robot or physical system you helped build. Describe the parts you owned, the integration challenges and how the system was tested. A demonstration, code sample or account of a difficult hardware-software failure is useful.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Robotics+Engineer\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Robot integration",
        "Control systems",
        "Policy deployment"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Robotics+Engineer"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/hardware-engineer-electronics/",
      "url": "https://www.goodailabs.com/careers/hardware-engineer-electronics/",
      "title": "Hardware Engineer, Electronics & Embedded Systems",
      "summary": "Design and bring up the electronics that connect robot sensing, compute and actuation.",
      "content_html": "<p>We are looking for a Hardware Engineer to develop electronics and embedded systems for robotics. You will take designs from electrical requirements and component selection through schematics, board bring-up and integration with the rest of the robot.</p><p>The work covers sensing, power, communication and the embedded interfaces that connect computation to physical behaviour. You will make design decisions, work directly on prototypes and resolve issues at the bench. Close collaboration with mechanical and robotics engineers will be essential as requirements and experiments evolve.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Define electrical requirements and select components for sensing, power distribution, communication and actuator interfaces.</li><li>Design schematics and PCBs, considering grounding, protection, signal integrity, connectors and mechanical constraints.</li><li>Develop embedded firmware and diagnostic tools for device bring-up, sensor acquisition and communication with robot software.</li><li>Plan and execute bench validation for power behaviour, timing, thermal performance and operation under relevant loads.</li><li>Investigate electrical and firmware faults with laboratory instruments, and carry findings through to a tested design revision.</li><li>Maintain bills of materials, fabrication and assembly documentation, and work with suppliers and engineers through prototype builds.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li><p>BS, MS or PhD in electrical engineering, computer engineering or a related field, or a substantial record of electronics design and embedded development.</p></li><li><p>Experience taking an electronic design through schematic development, fabrication, bring-up and testing.</p></li><li><p>Strong foundations in circuit design, power distribution and digital communication, with practical knowledge of PCB design and layout.</p></li><li><p>Embedded programming experience in C or C++, including microcontrollers and interfaces to sensors or actuators.</p></li><li><p>Confidence using oscilloscopes, logic analysers and other bench equipment to diagnose intermittent or system-level faults.</p></li><li><p>The ability to communicate design decisions through clear schematics, test results and revision records, and to resolve integration issues with other disciplines.</p></li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Robotics electronics, motor interfaces, sensor acquisition or embedded systems with timing constraints.</li><li>Communication buses, power conversion, protection circuits or electromechanical assemblies.</li><li>Supplier coordination, board assembly, design reviews or development of production and acceptance tests.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and an electronic or embedded system you designed. Describe your responsibility, the design constraints and the work involved in bringing it into operation. Schematics, board photographs, firmware or test results are welcome where you have permission to share them.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Hardware+Engineer%2C+Electronics+%26+Embedded+Systems\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Robot electronics",
        "Embedded firmware",
        "Hardware validation"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Hardware+Engineer%2C+Electronics+%26+Embedded+Systems"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/mechanical-engineer-robotics/",
      "url": "https://www.goodailabs.com/careers/mechanical-engineer-robotics/",
      "title": "Mechanical Engineer, Robotics",
      "summary": "Own mechanical designs from concept to tested hardware, building the mechanisms and assemblies that robots depend on.",
      "content_html": "<p>We are hiring a Mechanical Engineer to design and develop robotics hardware. You will take responsibility for mechanisms, structures and assemblies from initial requirements through CAD, fabrication, assembly and physical testing.</p><p>The role combines analytical design with practical work on prototypes. You will need to understand how loads, motion, tolerances and packaging affect the robot, while making hardware that can be assembled, instrumented and revised as research progresses. You will work closely with electronics and robotics engineers, as well as suppliers responsible for making the parts.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop mechanisms and structural assemblies that meet requirements for motion, load capacity, stiffness, weight and packaging.</li><li>Use calculations and simulation where appropriate to compare concepts and guide design choices before fabrication.</li><li>Produce detailed CAD, drawings and tolerance specifications that manufacturers can build and inspectors can verify.</li><li>Select materials and manufacturing processes with attention to performance, lead time, cost and the needs of prototype development.</li><li>Build and test assemblies and fixtures, investigating deflection, wear, range of motion and other relevant failure modes.</li><li>Resolve integration issues involving sensors, actuators, electronics, cable routing and service access; maintain clear revision and assembly records.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li><p>BS, MS or PhD in mechanical engineering, robotics or a related field, or demonstrated design and hardware-development work of equivalent depth.</p></li><li><p>Experience delivering mechanical designs through fabrication, assembly and testing, with direct ownership of the engineering work.</p></li><li><p>Strong CAD skills and the ability to create complete drawings, tolerance schemes and assembly documentation.</p></li><li><p>A sound understanding of mechanics, material behaviour and common manufacturing processes.</p></li><li><p>The ability to use both analysis and physical measurements to evaluate a design and investigate unexpected behaviour.</p></li><li><p>Practical experience working with suppliers and other engineering disciplines, including hands-on involvement in prototype builds.</p></li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Robot mechanisms, actuation systems, end effectors or electromechanical packaging.</li><li>Structural analysis, tolerance stack-ups, design for assembly or selection of bearings, transmissions and fasteners.</li><li>Test rigs, prototype fabrication or improving the reliability and serviceability of moving machinery.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and examples of hardware you designed. Explain the requirements, your contribution and the most consequential design decisions. Include drawings, prototype photographs and a brief account of physical testing where available.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Mechanical+Engineer%2C+Robotics\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Mechanism design",
        "Prototype development",
        "Physical testing"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Mechanical+Engineer%2C+Robotics"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/customer-engineer/",
      "url": "https://www.goodailabs.com/careers/customer-engineer/",
      "title": "Customer Engineer, AI & Robotics",
      "summary": "Turn robotics use cases into working integrations, rigorous evaluations and a clear path to deployment.",
      "content_html": "<p>We are looking for a Customer Engineer to help prospective customers evaluate and integrate foundational models and systems for robotics. You will work directly with technical teams to understand the application, build a useful prototype and establish what is required for it to work in their environment.</p><p>The role combines software engineering with technical communication. You will move between discovery discussions, implementation and hands-on debugging, working with research and robotics engineers when an evaluation exposes a limitation. The aim is to give prospective customers a well-founded basis for a deployment decision and give our team a clear understanding of their needs.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Lead technical discovery for robotics and AI applications, identifying the task, hardware, data, integration constraints and acceptance criteria.</li><li>Build prototype integrations and reference applications using model interfaces, APIs and the tools available in the customer environment.</li><li>Design and run evaluations of task performance, latency, memory use and failure behaviour under representative conditions.</li><li>Diagnose problems across application code, model execution, data and infrastructure; produce actionable reports for research and engineering.</li><li>Explain results and trade-offs to technical and commercial stakeholders, including the work needed to move beyond an evaluation.</li><li>Develop setup guides, reusable examples and handover documentation that reduce the effort required for subsequent integrations.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li><p>BS, MS or PhD in computer science, engineering or a related field, or equivalent experience delivering technical integrations.</p></li><li><p>Strong software engineering skills, with experience delivering integrations or applications involving machine-learning models.</p></li><li><p>Proficiency in Python and comfort working with APIs, Linux, model runtimes and unfamiliar customer systems.</p></li><li><p>Experience leading technical discussions, clarifying requirements and turning them into an implementation and test plan.</p></li><li><p>The ability to debug across system boundaries and distinguish model limitations from integration or data problems.</p></li><li><p>Clear written and verbal communication, including explaining technical trade-offs to people with different levels of expertise.</p></li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Customer engineering, solutions engineering, field engineering or technical work with robotics and automation teams.</li><li>Computer vision, robot software, inference deployment or applications that use agents and external tools.</li><li>Evaluations with constraints on compute, connectivity, data access or operational downtime.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and an integration or technical evaluation you delivered. Describe the application, what you built and how the work informed the customer’s next decision. An anonymised case study, architecture diagram or code example is welcome.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Customer+Engineer%2C+AI+%26+Robotics\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Technical evaluation",
        "Model integration",
        "Robotics applications"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Customer+Engineer%2C+AI+%26+Robotics"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/technical-sales-lead/",
      "url": "https://www.goodailabs.com/careers/technical-sales-lead/",
      "title": "Technical Sales Lead, AI & Robotics",
      "summary": "Build the commercial pipeline for our robotics and AI work, from identifying the right applications to negotiating agreements.",
      "content_html": "<p>We are hiring a Technical Sales Lead to develop commercial opportunities for Good AI Labs’ models and systems. You will identify organisations with a clear need for our work, build relationships with technical and business decision-makers, and lead opportunities from first discussion through evaluation and agreement.</p><p>This is a hands-on role for someone who understands how engineering organisations buy and adopt new technology. You will help determine where our capabilities can create value, work with engineers to establish technical fit and build a disciplined commercial process as the company develops its robotics business.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Identify and develop opportunities with robotics companies, integrators and organisations pursuing relevant automation applications.</li><li>Lead discovery to understand the customer’s task, current approach, expected value, budget and decision process.</li><li>Build relationships with technical champions, commercial buyers and procurement teams, maintaining a clear plan for each opportunity.</li><li>Work with customer engineers and researchers to scope evaluations with agreed success criteria, responsibilities and next steps.</li><li>Develop proposals, negotiate commercial terms and coordinate the work required to reach an agreement.</li><li>Maintain an accurate pipeline and forecast, and bring recurring customer needs back into discussions about product and research priorities.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>A record of personally developing and closing complex technical sales in AI, robotics, industrial technology or enterprise software.</li><li>Experience managing opportunities that involve technical evaluation, several stakeholders and a formal purchasing process.</li><li>Sufficient technical depth to discuss model capabilities, integration requirements and deployment economics with engineering teams.</li><li>Strong commercial judgement, including qualification, negotiation, forecasting and the ability to decide when an opportunity is a poor fit.</li><li>Clear, persuasive writing and the ability to build trust with customers while coordinating closely with a technical team.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Building an initial sales pipeline or commercial process at an early-stage technology company.</li><li>Selling to robotics developers, automation teams, hardware companies or buyers of research-driven technology.</li><li>Structuring evaluations and commercial agreements where technical performance is central to the buying decision.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and a short account of one or two technical deals you led. Describe the customer’s need, the sales process, your contribution and the outcome. Anonymised examples are welcome. Tell us where you see the strongest commercial opportunity for more capable robot intelligence.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Technical+Sales+Lead%2C+AI+%26+Robotics\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Technical sales",
        "Customer discovery",
        "Commercial agreements"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Technical+Sales+Lead%2C+AI+%26+Robotics"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/research-industry-partnerships/",
      "url": "https://www.goodailabs.com/careers/research-industry-partnerships/",
      "title": "Partnerships Lead, Research & Industry",
      "summary": "Build research and industry partnerships that connect our models to expertise, hardware and meaningful robotics applications.",
      "content_html": "<p>We are looking for a Partnerships Lead to develop collaborations that advance Good AI Labs’ robotics work. You will identify research groups, robot developers, hardware companies and industry organisations whose expertise or resources complement our own, and turn shared interests into substantive projects.</p><p>The work requires technical understanding and the ability to bring together people with different priorities. You will help define what each collaboration should accomplish, secure agreement on the work and remain involved as it is delivered. Potential projects include joint evaluations, research collaborations, hardware integrations and access to relevant application environments.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Develop a partnership strategy around the needs of our work in foundational models, simulation, robot learning and supporting systems.</li><li>Identify prospective collaborators and build relationships with the researchers, engineers and leaders who would participate in the work.</li><li>Define the technical objective, contribution from each party, required resources and expected benefit of a proposed collaboration.</li><li>Work with research and engineering teams to establish deliverables, ownership, milestones and criteria for evaluating the outcome.</li><li>Coordinate discussions about data access, intellectual property, publication and commercial terms with the relevant decision-makers and advisers.</li><li>Manage relationships through delivery, resolve dependencies and assess whether a collaboration merits expansion or a change in direction.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>Experience initiating and delivering technical partnerships, research collaborations or business-development agreements.</li><li>A strong understanding of AI, robotics, hardware or scientific computing, sufficient to assess a proposal and engage credibly with technical teams.</li><li>A record of turning an exploratory relationship into a defined project or agreement with a demonstrable outcome.</li><li>Strong negotiation and stakeholder management skills, including the ability to reconcile different incentives and resolve stalled discussions.</li><li>Clear writing and disciplined follow-through, with careful handling of confidential information and partner commitments.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Work across academic and industrial research, robotics ecosystems, semiconductor companies or hardware suppliers.</li><li>Joint development agreements, technology licensing or collaborations involving shared data and research outputs.</li><li>Building relationships across regions and establishing partnerships for an early-stage company.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and an example of a partnership you helped originate and deliver. Explain why the collaboration made sense, your role in shaping it and what it achieved. Tell us which kinds of partners you believe could most accelerate progress in robotics. Please anonymise confidential details.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Partnerships+Lead%2C+Research+%26+Industry\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Research partnerships",
        "Industry collaboration",
        "Joint development"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Partnerships+Lead%2C+Research+%26+Industry"
      }
    },
    {
      "id": "https://www.goodailabs.com/careers/supply-chain-logistics/",
      "url": "https://www.goodailabs.com/careers/supply-chain-logistics/",
      "title": "Operations Lead, Supply Chain & Logistics",
      "summary": "Build the sourcing and logistics operation that keeps robotics development supplied, traceable and on schedule.",
      "content_html": "<p>We are hiring an Operations Lead to establish and manage the supply chain supporting our robotics development. You will work with engineers to source components and fabricated parts, coordinate suppliers and keep track of the equipment and materials needed for prototype builds and testing.</p><p>This is a hands-on role spanning procurement, inventory and logistics. You will need to manage changing requirements, long lead times and the practical details of moving technical equipment between suppliers and the people using it. The objective is a dependable operation that gives the engineering team a clear view of availability, cost and delivery risk.</p><h2 id=\"responsibilities\">Responsibilities</h2><ul><li>Translate bills of materials and engineering plans into sourcing priorities, purchase schedules and delivery commitments.</li><li>Identify and assess suppliers for technical fit, quality, cost and lead time, working with engineers to approve alternatives and substitutions.</li><li>Manage enquiries, quotations, purchase orders and supplier follow-up, keeping revision, quantity and approval records accurate.</li><li>Coordinate shipping, receiving, inspection, inventory and returns so parts can be traced to the builds they support.</li><li>Work with logistics providers and appropriate specialists on packaging, shipping documentation and cross-border movements.</li><li>Track spend, shortages and schedule risks; resolve delivery problems and establish purchasing and inventory processes that remain useful as the work grows.</li></ul><h2 id=\"qualifications\">Qualifications</h2><ul><li>Experience owning procurement, supply-chain or logistics work for hardware development or another technical programme.</li><li>Practical familiarity with part specifications, bills of materials, supplier quotations and the consequences of revision changes.</li><li>Strong supplier communication and negotiation skills, with evidence of resolving shortages, quality issues or missed deliveries.</li><li>The ability to maintain reliable operational records and use them to explain cost, availability and schedule trade-offs.</li><li>Sound judgement under changing priorities and a record of following a problem through to its resolution.</li></ul><h2 id=\"experience-that-would-help\">Preferred experience</h2><ul><li>Electronics, mechanical fabrication, robotics equipment or procurement for low-volume prototype builds.</li><li>Cross-border sourcing and logistics, particularly across Asian hardware supply chains.</li><li>Establishing purchasing controls, inventory systems or supplier performance tracking in a growing organisation.</li></ul><h2 id=\"what-to-include-in-your-application\">Application materials</h2><p>Include your CV and an example of a supply-chain or logistics problem you owned. Describe the technical requirements, delivery constraints and actions you took, along with the effect on cost, timing or reliability. Use anonymised figures or supplier details where necessary.</p><section class=\"career-next\" aria-labelledby=\"career-next-title\"><h2 id=\"career-next-title\">How to apply</h2><p>Email your application to <a href=\"mailto:research@goodailabs.com\">research@goodailabs.com</a>, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.</p><a class=\"text-link\" href=\"mailto:research@goodailabs.com?subject=Application%3A+Operations+Lead%2C+Supply+Chain+%26+Logistics\">Apply for this role <span aria-hidden=\"true\">↗</span></a></section>",
      "date_published": "2026-10-13T00:00:00Z",
      "tags": [
        "Technical sourcing",
        "Prototype supply chain",
        "Logistics"
      ],
      "language": "en",
      "_application": {
        "url": "mailto:research@goodailabs.com?subject=Application%3A+Operations+Lead%2C+Supply+Chain+%26+Logistics"
      }
    }
  ]
}