Helix AI Engineer, Robot Learning

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA.

We are looking for a Helix AI Engineer, Robot Learning with a strong robotics learning background to help develop and improve our visuomotor manipulation policies, with a heavy emphasis on real-robot deployment.

• →Design, train, evaluate, and deploy learning-based visuomotor policies for humanoid robot manipulation
• →Develop manipulation behaviors such as grasping, pick-and-place, object reorientation, door opening, bimanual manipulation, and basic assembly
• →Apply and extend techniques including behavior cloning, reinforcement learning, and VLA reasoning
  
• →Train models that are robust to real-world challenges such as sensor noise, partial observability, contact dynamics, and environment variability
• →Own the full pipeline from data collection on real robots to model training, evaluation, and deployment
• →Work closely with simulation and digital twin tooling where useful, while prioritizing real-world performance and transfer
  
• →Collaborate with perception, controls, systems, and hardware teams to integrate policies into a full autonomy stack
• →Evaluate tradeoffs between learning-based and classical approaches and make principled design decisions
• →Write high-quality, well-tested software that ships to and runs reliably on physical humanoid robots
• →Partner with integration and testing teams to continuously improve robustness, performance, and deployment velocity

• Hands-on experience developing and deploying robot learning systems on real robots
  
• Strong background in robot manipulation and visuomotor control
  
• Experience with behavior cloning, reinforcement learning, or related learning-based manipulation methods
• Proficiency in Python and/or C++ for robotics and ML systems
• Experience with modern deep learning frameworks (e.g., PyTorch)
• Ability to design experiments, analyze failures, and iterate quickly in real-world robotic systems
• Solid understanding of the tradeoffs between classical robotics approaches and learning-based methods
• Thrive in fast-paced, ambiguous environments where solutions require exploration and ownership

• Experience deploying learning-based manipulation systems in commercial or production robotic systems
  
• Prior work on humanoids or highly dexterous robotic platforms
• Publication record in robot learning, manipulation, or embodied AI
• Experience leading projects or mentoring other engineers
• Passion for building autonomous humanoid robots that operate in the real world

The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.