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Helix AI Engineer, Robot Learning

Figureai4h ago
United StatesOnsiteFull-time

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Ai EngineerDeep Learning EngineerSenior Ml EngineerRl EngineerMl Engineer
  • 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 .
  • Responsibilities
  • 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
  • Requirements
  • 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
  • Bonus Qualifications
  • 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
  • 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.

Required skills

robot learningvisuomotor manipulationbehavior cloningreinforcement learningPythonC++deep learningPyTorch
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