The company is looking to enhance physics simulation tools for robotic autonomy and bridge the gap between simulation and real-world environments.
Requirements
- Proficiency in modern C++ (C++14/17/20) and Python.
- Experience in GPU accelerated physics and rendering.
- Familiarity with machine learning techniques and optimization methods to enhance simulation accuracy and bridge the sim-to-real gap.
- Experience in system-level optimization through multi-threading, asynchronous programming, concurrency, and parallelism.
- Proficiency with one or more physical simulators (e.g., MuJoCo, IsaacSim, Drake, PyBullet, PhysX)
- Expertise in deployed robotics environments.
- Experience in reinforcement learning, imitation learning or motion planning and control systems.
Responsibilities
- Build large scale synthetic data generation pipeline, work closely with AI team on iterating data quality.
- Build large scale photo-realistic and physics-based simulator.
- Investigate and address sim to real gaps.
- Stay current with and apply the latest advancements and technologies in humanoid robotics and simulation.
Other
- Bachelor’s or Master’s degree in Computer Science, Robotics, or related field.
- Requires 5 days/week in-office collaboration with the teams.
