Helix AI Engineer, Robot Learning

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.

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, 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.