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Veeda AI is building multimodal foundation world models for Physical AI, combining advances in machine learning with practical robotics and embodied intelligence. The company is a small, fast-moving team of engineers and researchers from leading AI labs.
In this Member of Technical Staff role, you will own critical robotics systems and data-collection workflows that support research and evaluation. Your responsibilities include:
- Building and maintaining robotic systems and data-collection infrastructure that enable research and evaluation at scale.
- Designing and executing hardware experiments to assess model performance, robustness, and generalization across real-world conditions.
- Developing reproducible benchmarks, investigating failure modes, and translating findings into actionable improvements for models and systems.
- Collaborating closely with researchers and engineers to bridge advances in machine learning with practical robotics challenges.
You will have the opportunity to make an outsized impact from day one, working on some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence.
REQUIREMENTS:
- PhD degree or equivalent hands-on experience in Robotics, Computer Science, Mechanical or Electrical Engineering, or a related technical field.
- Demonstrated experience developing learning-based robot policies and deploying them on real hardware.
- Strong Python and PyTorch skills, with proficiency in a robot software stack.
- Solid understanding of robot kinematics, sensing, calibration, and system integration.
- Ability to independently design, execute, and analyze reproducible robotics experiments.
- Willingness and ability to travel for hands-on robot setup, testing, and deployment.
NICE TO HAVE:
- Experience with manipulation, locomotion, or whole-body control.
- Experience establishing a robotics lab or data-collection operation from scratch.
- Experience with imitation learning, reinforcement learning, or robot foundation models.
- Experience with robotics simulation and transferring learned behaviors across environments.
- Experience working with multimodal sensor data, teleoperation systems, or tactile and force feedback.
- Publications or substantial contributions to research on robot learning or embodied AI.
- Contributions to open-source robotics projects or research infrastructure.
