Research Engineer / Scientist – Robotics & Physical AI

About the role

This is a hands‑on research and engineering position at an early‑stage AI data company focused on robotics and physical AI. You will work across learning algorithms, simulation, and hardware to move robot capabilities from simulation to real‑world deployment.

Key responsibilities

• Develop learning systems for robots, including policies, world models, and vision‑language‑action models.
• Build and maintain simulation environments and evaluation frameworks for robotic tasks.
• Apply and advance computer‑vision and perception algorithms for autonomous robots.
• Create pipelines that connect simulation and real‑world robot deployment (real‑to‑sim and sim‑to‑real).
• Work directly with robot hardware, sensors, actuators, and embedded systems to prototype and test capabilities.
• Train and evaluate reinforcement‑learning and imitation‑learning systems for manipulation, locomotion, or mobile platforms.
• Integrate robot platforms to validate algorithms in the physical world.
• Create tools and infrastructure that accelerate robotics research and development.
• Collaborate with external robotics companies and research labs on technical challenges.

Required profile

• Strong software skills in C++ and Python.
• Practical experience with deep learning, reinforcement learning, and computer vision.
• Hands‑on robotics research and engineering experience beyond academic prototypes.
• Experience with real‑to‑sim and sim‑to‑real workflows; familiarity with Isaac Lab, MuJoCo, MJX, or Genesis is a plus.
• Mechanical and hardware engineering experience, including sensors, actuators, CAD, and embedded systems.
• Industry experience in a company environment rather than solely university research.
• Ability to work as an individual contributor with end‑to‑end ownership in a fast‑moving small team.
• Exposure to modern multimodal AI approaches (transformers, diffusion models, world models, LLMs, AI agents) is a bonus.

Required skills

• C++
• Python
• Deep learning
• Reinforcement learning
• Computer vision
• Isaac Lab
• MuJoCo
• MJX
• Genesis
• CAD
• Sensors
• Actuators
• Embedded systems
• Transformers
• Diffusion models
• World models
• Large language models (LLMs)
• AI agents