Careers

Build intelligence for the physical world.

Help us build towards human-level robot intelligence and beyond.

At Reward AI, we are building frontier intelligence for any robot. Our work brings together machine learning, robotics, and hardware to help robots learn from people and perform useful work across bodies, tasks, and environments.

We welcome researchers, engineers, and people with experience in operations and product from a wide range of backgrounds. The qualifications below are starting points for a conversation. You do not need to match every item to apply.

Open roles

5 opportunities

Machine Learning Research Scientist and Engineer

Job description

Advance the models, data, and systems that help AI understand the world, reason, and act. This role spans foundational research and practical engineering, with opportunities across large language models (LLMs), vision-language models (VLMs), multimodal learning, foundation models, data engineering, and robot learning. Robotics-focused work includes imitation learning from human demonstrations, reinforcement learning, and policies that generalize across tasks and robot bodies. You could develop new modeling approaches, build data pipelines, scale training and inference, or create better ways to evaluate and improve models. Your work will contribute to Reward AI’s mission of building general robot intelligence, with a scope shaped around your strengths. Prior robotics experience is welcome but not required.

Responsibilities

  • Contribute across model research, data engineering, or ML systems, depending on your strengths and interests.
  • Develop and improve foundation models through pretraining, fine-tuning, post-training, or new approaches to learning and reasoning.
  • Explore robot learning methods such as imitation learning, behavior cloning, reinforcement learning, and learning from human video to develop generalizable manipulation and whole-body skills.
  • Build scalable pipelines for collecting, processing, curating, and serving diverse datasets, including text, images, video, and other modalities.
  • Design experiments and evaluations, analyze model behavior and data quality, and improve training or inference efficiency and reliability.
  • Collaborate with researchers and robotics engineers to evaluate models in simulation and on real robots, translate advances in general AI into useful capabilities, and shape technical priorities.

Preferred qualifications

  • A foundation in machine learning, computer science, data engineering, mathematics, or a related area, developed through study or practical work.
  • Experience in one or more of LLMs, VLMs, foundation models, multimodal learning, computer vision, imitation learning, reinforcement learning, robot learning, or data engineering. Depth in any one area is valuable; experience across all of them is not expected.
  • Strong programming skills and experience building models, data pipelines, or scalable software systems. Relevant tools may include Python, SQL, PyTorch, JAX, or distributed data processing frameworks.
  • Evidence of thoughtful research or strong engineering through projects, publications, open-source contributions, or deployed systems.
  • Curiosity, clear communication, and the ability to turn open-ended questions into concrete experiments.

Mechanical Engineer

Job description

Design and build the physical systems that make robot intelligence useful. You will work across robot hardware, mechanisms, end effectors, and research equipment, taking ideas from early concepts through prototypes, testing, and reliable assemblies. This is a hands-on role with room to contribute across design, integration, and manufacturing as our needs evolve.

Responsibilities

  • Develop mechanical concepts, CAD models, drawings, and assemblies for robots and the tools used to build and evaluate them.
  • Prototype, assemble, and test hardware, using experimental results to improve performance, durability, and ease of use.
  • Evaluate design tradeoffs through structural, thermal, tolerance, or motion analysis as appropriate.
  • Work with electrical, software, and research teammates to integrate actuators, sensors, wiring, and other components.
  • Collaborate with suppliers and fabrication partners, and maintain documentation that supports repeatable builds, service, and manufacturing.

Preferred qualifications

  • A foundation in mechanical engineering, mechatronics, or a related field, gained through education, industry, or independent projects.
  • Experience with 3D CAD and taking a design from an initial idea to working hardware.
  • Familiarity with materials, manufacturing processes, rapid prototyping, and design for assembly and maintenance.
  • Hands-on experience with mechanisms, actuators, robotic systems, or other electromechanical products.
  • Practical problem-solving skills, attention to detail, and a collaborative approach to building and debugging physical systems.

Humanoid Research Scientist and Engineer

Job description

Help humanoid robots move and work with greater capability, adaptability, and reliability. You will connect learning, control, and physical systems to develop behaviors that combine locomotion and manipulation. The role spans research and implementation, with opportunities to work in simulation and on real robots across the path from an initial experiment to repeatable behavior.

Responsibilities

  • Develop methods for whole-body control, locomotion, dexterous manipulation, and coordinated movement.
  • Build training and evaluation workflows using simulation, human motion, and other relevant data sources.
  • Investigate transfer from simulation to hardware and improve robustness to changes in contact, objects, terrain, and robot dynamics.
  • Integrate learned behaviors with perception, state estimation, planning, and real-time control systems.
  • Run hardware experiments with appropriate safeguards, diagnose failures, and work with the team to improve robot capability and reliability.

Preferred qualifications

  • A background in robotics, controls, machine learning, mechanical engineering, or a related field through research or practical experience.
  • Experience in one or more of robot learning, dynamics, motion planning, optimal control, or state estimation.
  • Ability to develop and debug robotics software in Python or C++, with familiarity with simulation or deep learning tools.
  • Hands-on work with humanoids, legged robots, manipulators, or other complex robotic systems.
  • Evidence of building and evaluating working systems, sound experimental judgment, and an interest in solving problems across software and hardware.

Data/Robot Operations

Job description

Manage the data collection and model evaluation that help our robots learn and improve. You will organize collection sessions, operate robots and recording equipment, maintain data quality, and run repeatable evaluations of new models. Working closely with researchers and engineers, you will turn observations from real robot behavior into useful feedback and help build reliable workflows as we scale.

Responsibilities

  • Plan and coordinate data collection across tasks, environments, and robot platforms with the research team.
  • Set up and operate robots, teleoperation systems, and recording equipment, following operating procedures and safety practices.
  • Review demonstrations and recordings for quality, organize datasets, and track collection progress and coverage.
  • Run model evaluations on real robots, record outcomes, and document failures so the team can compare results across model versions.
  • Troubleshoot operational issues with engineers and improve collection instructions, evaluation procedures, and equipment readiness.

Preferred qualifications

  • Experience in robotics operations, data collection, lab operations, quality assurance, or another hands-on technical environment.
  • Strong organization and attention to detail, with an ability to follow and improve repeatable processes.
  • Comfort working with physical hardware, learning new tools, and diagnosing practical problems.
  • Ability to document results clearly and communicate observations to research and engineering teammates.
  • Familiarity with spreadsheets, data tools, or basic scripting is helpful. Prior robot operation or teleoperation experience is welcome but not required.

Product

Job description

Help bring general robot intelligence to customers through go-to-market strategy and hands-on customer support. You will work with the team to identify useful applications, understand customer needs, shape how we introduce our capabilities, and support customers from early conversations through pilots and ongoing use. This role connects product direction with real-world feedback, helping us focus on work that delivers value.

Responsibilities

  • Develop and refine go-to-market strategy, including target customers, use cases, positioning, and launch priorities.
  • Talk with prospective and existing customers to understand their workflows, needs, and measures of success.
  • Coordinate product demonstrations, onboarding, and pilots with research and engineering teammates.
  • Support customers by answering questions, documenting issues, coordinating technical follow-up, and improving guides and support materials.
  • Turn customer feedback and pilot results into clear product requirements and recommendations for what to build next.

Preferred qualifications

  • Experience in product management, go-to-market strategy, customer success, technical support, or a related role.
  • Strong communication skills and an ability to explain technical capabilities clearly to different audiences.
  • A practical approach to customer discovery, prioritization, and measuring whether a product solves a useful problem.
  • Comfort working with technical teams and learning about AI and robotics. Prior experience in either field is helpful but not required.
  • Initiative, sound judgment, and a willingness to move between strategy and day-to-day customer support as needs evolve.

Apply to Reward AI

Apply using the form below. Please include your name, email, role, resume, a brief introduction, why you want to work at Reward AI, and one or two accomplishments you are proud of. Links to your work are optional.

You can also open the application form in a new tab . For questions, contact careers@rewardai.com.

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