Join to apply for the AI Training Infrastructure Engineer - Helix Team role at Figure Join to apply for the AI Training Infrastructure Engineer - Helix Team role at Figure Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose, CA and require 5 days/week in-office collaboration. It’s time to build.

Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Training Infrastructure Engineer, to take our infrastructure to the next level. This role is focused on managing the training cluster, implementing distributed training algorithms, data loaders, and developer tools for AI researchers. The ideal candidate has experience building tools and infrastructure for a large-scale deep learning system.

Responsibilities

Design, deploy, and maintain Figure's training clusters Architect and maintain scalable deep learning frameworks for training on massive robot datasets Work together with AI researchers to implement training of new model architectures at a large scale Implement distributed training and parallelization strategies to reduce model development cycles Implement tooling for data processing, model experimentation, and continuous integration

Requirements

Strong software engineering fundamentals Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field Experience with Python and PyTorch Experience managing HPC clusters for deep neural network training Minimum of 4 years of professional, full-time experience building reliable backend systems

Bonus Qualifications

Experience managing cloud infrastructure (AWS, Azure, GCP) Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.) Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.)

The US base salary range for this full-time position is between $150,000 - $350,000 annually.

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. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Information Technology Industries Machinery Manufacturing Referrals increase your chances of interviewing at Figure by 2x Get notified about new Infrastructure Engineer jobs in San Jose, CA . Software Engineer, AI Intern (Fall 2025) San Francisco Bay Area $57.00-$61.00 2 weeks ago Mountain View, CA $125,400.00-$188,100.00 2 weeks ago Software Engineer, AI Platform - New Grad San Jose, CA $130,000.00-$180,000.00 2 weeks ago New Grads 2025 - Software Engineer, Algorithm San Jose, CA $120,000.00-$165,000.00 9 months ago New Grads 2025 - General Software Engineer San Jose, CA $120,000.00-$165,000.00 5 months ago Software Engineer (L4), Content & Business Products Full Stack Software Engineer - Post-training San Jose, CA $142,400.00-$190,100.00 2 weeks ago Palo Alto, CA $96,000.00-$200,000.00 2 weeks ago Software Engineer 4 - TV & Web Player Platform Software Engineer - Intern (Summer 2025) San Jose, CA $3,000.00-$4,000.00 8 months ago San Jose, CA $113,400.00-$206,300.00 2 weeks ago San Jose, CA $113,400.00-$206,300.00 1 week ago San Jose, CA $113,400.00-$206,300.00 2 weeks ago San Jose, CA $113,400.00-$206,300.00 2 weeks ago San Jose, CA $100,500.00-$173,250.00 1 week ago Software Engineer(s) - New Grad (Fall 2025 Graduation) San Jose, CA $133,900.00-$242,000.00 1 day ago Palo Alto, CA $152,400.00-$228,700.00 2 weeks ago Sunnyvale, CA $117,000.00-$234,000.00 2 weeks ago Santa Clara, CA $150,000.00-$175,000.00 7 months ago eCommerce Full Stack Developer (React / Shopify) - On Site San Jose, CA $126,000.00-$276,000.00 4 days ago Full Stack Software Engineer (L4), Product Localization Engineering We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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