Position Summary

Adept is building a new class of multimodal AI models designed specifically for digital agents. Our model iteration speed depends on training performance while using some of the largest GPU clusters around. Engineers with a background in distributed deep learning (DL) training can help Adept iterate faster. Areas of focus on the Infrastructure team include:

• Compute - building and managing large GPU clusters training SOTA models
• Optimization - improving the DL training utilization and reliability of those clusters
• Research - working directly with researchers to align model architecture with training performance

We value curious engineers who can engage with new problems and get things done at a startup. Our team members come from a variety of backgrounds. If you have some of these, you might be a good fit:

• 8+ years of experience as a software engineer
• Expert understanding of distributed training concepts and tools, e.g., torch.distributed, NCCL, MPI, etc.
• Experience with GPU cluster hardware, performance, interconnect, etc.
• Track record at fast-growing companies or startups
• Demonstrated end-to-end ownership and self-direction
• Comfort with moving fast and learning by doing
• Excellent communication and collaboration skills, both verbal and written

The pay range for this position in California is $175,000 - $350,000yr; however, base pay offered may vary depending on job-related knowledge, skills, candidate location, and experience. We also offer competitive equity packages in the form of stock options and a comprehensive benefits plan.