Research​/Software Engineer - Humanoid Body Learning

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment.

Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.

FieldAI is seeking a Software/Research Engineer to help build the learning systems that power our next generation of humanoid robots. You'll work across whole-body loco-manipulation, reinforcement learning, motion retargeting, and real-world robot deployment, turning new research and technical developments into reliable capabilities on physical humanoids. This is a highly hands-on role for someone excited about closing the loop between research, simulation, and robots operating in the real world.

• Develop and train whole-body loco-manipulation policies for humanoid robots.
• Deploy trained policies to physical humanoids and integrate them into our production software stack.
• Advance our motion retargeting pipeline, transforming human motion into physically plausible, robot-executable behaviors that interact with diverse environments and objects.
• Reduce the sim-to-real gap by improving simulation fidelity and closing the real-to-sim loop, using real-world robot data to calibrate and refine our simulators.
• Build automated evaluation and validation systems that make it faster and more reliable to move policies from simulation onto physical robots.
• Improve the performance and scalability of our robot-learning infrastructure, enabling faster experimentation and policy iteration.
• Work closely with researchers and engineers across perception, learning, simulation, and hardware to turn new ideas into deployed robot capabilities.

• BS, MS, or PhD in Robotics, Computer Science, Machine Learning, Engineering, or a related field, or equivalent experience.
• Experience with reinforcement learning, imitation learning, generative models, or other learning-based approaches for robotics.
• Strong understanding of robotics fundamentals such as kinematics, dynamics, control, and physical interaction.
• Experience developing and evaluating robotic systems in simulation and/or on physical hardware.
• Ability to move comfortably between research experimentation and production-quality engineering.

• Hands-on experience with humanoid robots.
• Experience with whole-body loco-manipulation.
• Experience with GPU-accelerated simulation frameworks such as NVIDIA Isaac Sim, Isaac Lab, and/or Newton.
• Experience with motion retargeting.
• Experience taking learned robot behaviors from simulation to real hardware.
• Experience building scalable RL training, evaluation, and/or automated robot-testing infrastructure.

$120,000 - $220,000 a year

FieldAI is tackling one of robotics’ hardest problems: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ advance perception, planning, localization, and manipulation with an emphasis on explainability and safety, so our systems can be trusted where it matters most.

You will work alongside a world-class team that values creativity, resilience, and bold thinking. We bring a decade-long track record of real-world deployments, strong performance in DARPA challenges, and experience from organizations such as Deep Mind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and…