Helix AI Engineer, Modeling

About the role

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is to build embodied AI systems that can perceive, reason, and act in the real world. Figure is headquartered in San Jose, CA, and this role requires 5 days/week in-office collaboration.

Our Helix team is responsible for developing the core AI systems that power humanoid autonomy. We are looking for a Helix AI Engineer, Modeling to design and advance the core model architectures and learning approaches that enable perception, reasoning, and action in embodied systems.

This role focuses on developing new modeling approaches across vision, language, and action—spanning representation learning, multimodal fusion, and model capabilities that directly impact robot intelligence.

Responsibilities

Design and develop model architectures for perception, reasoning, and action across multimodal inputs (e.g., vision, language, proprioception)

Build models that learn structured representations of the world, including objects, dynamics, and interactions

Advance multimodal learning approaches, including fusion, alignment, and cross-modal reasoning

Improve model capabilities in areas such as generalization, robustness, and long-horizon reasoning

Work across the model lifecycle, from initial research and prototyping to training and deployment

Collaborate closely with pretraining, video, generative, RL, and robot learning teams to integrate modeling advances into the full autonomy stack

Design experiments and evaluation frameworks to understand model behavior and guide iteration

Contribute to the development of new modeling paradigms for embodied AI systems

Requirements

Experience designing and training deep learning models for vision, language, or multimodal systems

Strong understanding of modern model architectures (e.g., transformers and related approaches)

Experience improving model performance through architectural innovation and experimentation

Proficiency in Python and deep learning frameworks such as PyTorch

Strong experimental rigor and ability to iterate on model design and performance

Solid software engineering skills and ability to build reliable, maintainable systems

Ability to operate independently and drive ambiguous, high-impact technical problems

Bonus Qualifications

Experience with multimodal models (vision-language or vision-language-action systems)

Background in representation learning, world models, or structured prediction

Experience working on frontier models at companies such as OpenAI, Google DeepMind, Anthropic, Meta, or xAI

Familiarity with embodied AI, robotics, or real-world ML systems

Experience with large-scale training or distributed systems

Publication record in machine learning, computer vision, NLP, or multimodal AI

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.