Helix AI Engineer, Generative AI

Figure; San Jose (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

An innovative AI robotics company is seeking a Helix AI Engineer, Generative AI to develop and scale generative models for humanoid robots. The role involves designing and deploying diffusion models, improving robot perception, and building synthetic data systems. Candidates should have experience in deep learning and Python, alongside strong software engineering skills. Offered position requires in-office collaboration in San Jose, CA, with the possibility of a competitive benefits package based on experience.

Qualifications

• Experience training and deploying generative models (diffusion, autoregressive).
• Strong understanding of techniques for vision and/or multimodal systems.
• Proficiency in Python and deep learning frameworks.

Responsibilities

• Design, train, and deploy large-scale generative models.
• Develop models that improve robot perception and world modeling.
• Build systems for synthetic data creation and dataset scaling.

Skills

Experience training and deploying generative models

Strong understanding of modern deep learning techniques

Proficiency in Python

Experience with large-scale datasets

Strong experimental rigor

Solid software engineering skills

Ability to operate independently

Tools

PyTorch

Job description

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, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on training and deploying diffusion and generative models across vision, video, and multimodal domains, with applications spanning perception, data generation, and model-based reasoning.

Responsibilities

• Design, train, and deploy large-scale generative models, with a focus on diffusion-based approaches for vision, video, and multimodal data
• Develop models that improve robot perception, world modeling, and prediction from raw sensory inputs
• Build generative systems for synthetic data creation, augmentation, and dataset scaling for robot learning
• Explore and implement state-of-the-art techniques in diffusion, generative modeling, and multimodal foundation models
• Work closely with data, training infrastructure, and agent teams to integrate generative models into the full autonomy stack
• Evaluate model quality, robustness, and generalization across real-world scenarios
• Contribute to the design of scalable experimentation frameworks for generative model development

Requirements

• Experience training and deploying generative models (diffusion, autoregressive, or related approaches) at scale
• Strong understanding of modern deep learning techniques for vision and/or multimodal systems
• Proficiency in Python and deep learning frameworks such as PyTorch
• Experience working with large-scale datasets and distributed training systems
• Strong experimental rigor and ability to iterate quickly on model performance
• Solid software engineering skills and ability to build reliable, maintainable systems
• Ability to operate independently and own ambiguous, high-impact technical problems

Bonus Qualifications

• Experience with diffusion models for image or video generation
• Experience with multimodal foundation models (vision-language or vision-language-action)
• Background in synthetic data generation or simulation for robotics or embodied AI
• Familiarity with 3D, video prediction, or world models
• Prior work in robotics, embodied AI, or real-world ML systems
• Publication record in machine learning, computer vision, or generative modeling

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.