The role
We are looking for a Principal Roboticist to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Labs as a founding member.
MEGA is building foundation models for general-purpose robots beyond self-driving vehicles. Our focus is on creating intelligent agents that can perceive, reason, move and manipulate the physical world across diverse embodiments, including mobile manipulators, dual-arm platforms and humanoids.
This is a senior, high-impact role with genuine 0→1 ownership. You will help define the research agenda, technical strategy and foundations of a new robotics program, working alongside world-class researchers in foundation models, embodied intelligence and large-scale machine learning.
You will have the opportunity to work across the entire robot stack: you will select, build, integrate, and maintain robot hardware; develop the software needed to deploy and test robot policies; and work closely with research teams to shape data collection, model evaluation, and the learning loop. The goal is work on compelling and publishable research, but also to turn it into systems that demonstrate increasingly general, robust and useful behavior in the physical world.
You will collaborate closely with researchers, ML engineers, roboticists and hardware teams to move ambitious ideas rapidly from research hypotheses to large-scale experiments and impressive real-world capabilities.
This is a rare opportunity to help build a general robotics effort from the ground up—combining frontier foundation-model research with the immediacy and complexity of intelligence embodied in real machines.
What you'll do
Build, integrate, and maintain robot hardware platforms for research and experimentation.
Develop and maintain robot software in C++ and Python, including control, planning, ROS/ROS2-based systems, and deployment infrastructure.
Create infrastructure for policy deployment, data collection, evaluation, and the robotics data flywheel.
Run real-world robot experiments and define data collection pilots that inform model development.
Collaborate with research teams on robot policy development, model evaluation, and data strategy.
Debug and troubleshoot robotic software, hardware, and policy failures.
Build robust deployment, regression, and validation tests for robot systems.
Help shape technical direction across robotics, ML, hardware, and experimentation.
What we're looking for
Experience in robot manipulation; working with robot hardware.
Experience leading robotics efforts.
Strong programming experience in C++ and/or Python.
Experience with robot software systems such as control, planning, ROS, or ROS2.
Experience in Machine Learning is welcome, in particular training and deploying learned robot policies.
A track record of high-quality research or engineering work in robotics, embodied AI, or related areas.
Publications in top-tier conferences such as ICRA, CoRL, or IROS are highly valued.
PhD preferred; Master's degree with equivalent experience also welcome.
5+ years of relevant industry experience.
What will make you successful
You enjoy working hands-on with real robots and are comfortable debugging across hardware, software, and ML systems.
You can move between research exploration and pragmatic engineering execution.
You have strong judgement around experiment design, data quality, and model evaluation.
You communicate clearly across research, engineering, and product teams.
You are excited by 0→1 ownership and ambiguity in a fast-moving research environment.
Why join us
Be part of a new, well-resourced initiative at the intersection of foundation models and robotics.
Work on generalist robot models and help build the systems that allow them to learn from real-world interaction.
Operate at serious scale with real robots, real data, and meaningful technical challenges.
Influence the full stack from ML research to hardware, deployment, and evaluation.
Join a research environment with space to innovate, publish, and define the future of embodied AI.
Location
This role is based in our Sunnyvale office and involves working closely with robotic lab infrastructure.
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