Position Summary

In this role, you'll be responsible for building the infrastructure critical to train and deploy large models reliably. You will build and improve the internal tooling to enable teams at Adept to efficiently leverage our large scale compute for use-cases ranging from distributed training to ML pipelines to petabyte-scale data processing to production inference. Some of this will be evaluating and improving existing solutions, but more commonly it will mean building systems either from nothing or to replace systems that are no longer appropriate at our organizational and computational scale. You will also work to ensure that our infrastructure is resilient to hardware failures, primarily by building software to identify and remediate issues, but also by manually diagnosing issues as needed and working with our compute partners to resolve any issues.

You'll be working closely with other researchers and engineers to push the frontier of machine learning capabilities and deploying them for useful applications.

Skills You'll Need to Bring (Qualifications):

• Extensive software design and engineering experience
• Experience with designing, building and/or running large scale distributed systems, preferably for machine learning systems
• Knowledge and experience with cloud infrastructure
• Willingness to manage and monitor infrastructure deployments
• Experience with machine learning frameworks and tools

The pay range for this position in California is $200,000- $225,000yr; however, base pay offered may vary depending on job-related knowledge, skills, candidate location, and experience. In addition to base salary, we also offer competitive equity and benefits packages.