Field AI
Research / Software Engineer - Humanoid Whole Body Learning
About this role
FieldAI seeks a Research/Software Engineer to develop learning systems for next-generation humanoid robots, focusing on whole-body loco-manipulation policies, motion retargeting, and sim-to-real transfer. You'll bridge research innovation and real-world deployment, working hands-on with physical robots and production infrastructure in Boston.
What you'll do
- Develop and train whole-body loco-manipulation policies for humanoid robots
- Deploy trained policies to physical humanoids and integrate into production software stack
- Advance motion retargeting pipelines to transform human motion into robot-executable behaviors
- Reduce sim-to-real gap by improving simulation fidelity and calibrating simulators with real-world data
- Build automated evaluation and validation systems for policy deployment
- Improve performance and scalability of robot-learning infrastructure
What they're looking for
- Reinforcement learning and imitation learning
- Robotics fundamentals (kinematics, dynamics, control, physical interaction)
- Simulation and physical robot development and evaluation
- GPU-accelerated simulation frameworks (NVIDIA Isaac Sim, Isaac Lab, Newton)
- Motion retargeting techniques
- Sim-to-real transfer and policy deployment
- Scalable RL training and evaluation infrastructure
- Software engineering in production environments
Benefits
- Work on cutting-edge humanoid robotics with real-world deployment
- Collaborate with world-class team from DeepMind, Boston Dynamics, NASA JPL, and leading tech companies
- Access to physical humanoid robots for hands-on experimentation
- Boston-based R&D team with distributed collaboration across Southern California and globally
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Field AI
Field AI develops embodied AI and autonomous robotics systems for real-world deployment in industrial environments like oil & gas and mining. The company is hiring software engineers to build web-based systems, perception and validation pipelines, test infrastructure, ROS-based robotic software, and customer-facing products that integrate AI with field-deployed hardware.
View all jobs at Field AILikely interview questions
- Describe your experience taking learned robot behaviors from simulation to real hardware—what were the biggest sim-to-real challenges you faced?
- Walk us through your experience with reinforcement learning or imitation learning in robotics; what algorithms and frameworks have you used?