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Robotics Autonomy Engineer - Manipulation
FieldAI
Irvine, USA
Full-time
Entry · 2+ years experience
Onsite
Discovered 1 weeks ago
Isaac LabMuJoCoDrakePythonC++Linux
Free
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Isaac LabMuJoCoDrake
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Isaac LabMuJoCoDrakePythonC++Linux
Full Job Posting
- Develop whole-body control and manipulation capabilities for humanoids and quadrupeds with arms, coordinating base, torso, and arm motion as a single system
- Take specific field scenarios from concept to repeatable execution on hardware, interacting with the built environment and handling objects and tools
- Build learning based and model based manipulation policies and integrate them tightly with perception and locomotion
- Train manipulation policies from demonstration data and adapt vision language action (VLA) foundation models to our robots and tasks, then make them work on hardware
- Design grasp, contact, and force interaction strategies that hold up across varied objects, surfaces, and environments, with interaction forces kept safe for people and equipment nearby
- Harden behaviors so they succeed across repeated runs, changing lighting, object variation, and real site conditions
- Build simulation environments and evaluation pipelines for manipulation, and use field data to close the gap between simulation and the real world
- Deploy on physical robots and iterate rapidly through lab testing and field validation
- Work closely with locomotion, perception, and systems engineers to deliver end to end capabilities
- Master’s degree or higher in Robotics, Computer Science, Engineering, or related field (PhD strongly preferred)
- Deep expertise in robot manipulation or whole-body control
- 2+ years of experience developing and deploying manipulation behaviors on real robotic systems (preferred)
- Hands-on experience with robot arms, hands or grippers, and humanoid or mobile manipulation platforms
- Solid understanding of kinematics, dynamics, contact modeling, and force control
- Experience with manipulation planning and control, such as trajectory optimization or model predictive control (MPC)
- Experience with learning based manipulation, such as imitation learning, reinforcement learning (RL), or vision language action models
- Proficiency with simulation tools such as Isaac Lab, MuJoCo, or Drake
- Experience integrating perception for manipulation
- Strong Python and/or C++ development skills in Linux-based development environments
- Familiarity with machine learning frameworks (PyTorch, JAX, TensorFlow)
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