
Helix AI Engineer, Robot Learning at Figure (San Jose, CA)
Figure· San Jose, CA·
Job description
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.
Why work at Figure
- Mission-Driven & High Impact: The company is laser-focused on a singular, ambitious mission: "to build the most groundbreaking company on the planet." Work is described as being "in the trenches together."
- Culture of Speed & Fearlessness: Core values include "Move Fast & Be Technically Fearless" and "Aggressively Optimistic." The environment is described as high-performance, with a "championship mindset."
- On-Site, Collaborative Environment: Employees work from physical offices in San Jose, CA (HQ) and a secondary location in Sunnyvale. The culture emphasizes in-person collaboration.
- Generous Benefits: Offers health insurance, generous parental leave, and family/childcare benefits.
- Massive Growth Trajectory: With 110 open roles, explosive headcount growth, and a clear path to market, employees have significant opportunity for career growth and impact.
- Technical Challenges: Work spans cutting-edge AI (reinforcement learning, perception, pretraining), hardware engineering (actuators, electrical, mechanical), and manufacturing at scale.