ScoutGet started
Figure AIAI - Helix Team

Helix AI Engineer, Robot Learning

$200k–$400kSan Jose, CA
Must-haves
  • 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

Nice to have: 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 role
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 US base salary range for this full-time position is between $200,000 - $400,000. 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.