Role Overview
Figureai is hiring a mid-level Helix AI Engineer, Training Infrastructure. This is a full-time role in San Jose. Part of Figureai's Ml Engineering hiring, posted 4 weeks ago. The posted range is $150k to $350k. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job description
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.
Responsibilities
- Design, deploy, and maintain Figure's training clusters
- Architect, optimize, 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, advanced parallelization strategies, and high-performance data loaders to reduce model development cycles
- Profile, identify, and eliminate training bottlenecks at the hardware and software levels to maximize Model FLOPs Utilization (MFU)
- Implement tooling for data processing, model experimentation, and continuous integration
- Strong software engineering fundamentals
- Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field
- Extensive professional experience with Python and PyTorch
- Proven track record of scaling and running large-scale training experiments personally on 800+ GPUs
- Experience managing HPC clusters for deep neural network training
- Minimum of 4 years of professional, full-time experience building reliable backend systems and infrastructure
- Experience contributing to or maintaining open-source distributed training frameworks (Megatron-LM, DeepSpeed, TorchTitan)
- 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.)
- Deep understanding of CUDA and hands-on experience writing custom GPU kernels to optimize training
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.
About Figureai
Figureai
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Frequently Asked Questions
How do I apply for the Helix AI Engineer, Training Infrastructure position at Figureai?
Use the Apply button above to submit your application directly to Figureai. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Helix AI Engineer, Training Infrastructure position at Figureai located?
This position is based in San Jose. Figureai has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
How much does the Helix AI Engineer, Training Infrastructure role at Figureai pay?
Figureai has posted a compensation range of $150k to $350k for this position. Final offers typically vary based on candidate experience, location, and internal salary bands.
When was the Helix AI Engineer, Training Infrastructure role at Figureai posted?
This role was posted on June 10, 2026 (29 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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