Software Engineer, Machine Learning Infrastructure
San Francisco /
Adept is an ML research and product lab building general intelligence by enabling humans and computers to work together creatively. We’ve raised a $65M Series A from Greylock and Addition and several angel investors, and were recently highlighted by Fortune.
We're looking for team members who are energized by our ambitious mission and excited to join a fast-paced startup environment, working closely together in our new office in San Francisco.
About the role
In this role, you'll be responsible for building large-scale systems for machine learning from the ground up--these are critical to train and deploy large models reliably. You'll be responsible for building infrastructure for our training/serving framework, improving the efficiency of running experiments, and building scale-oriented tooling across multiple teams. You'll be working closely with other researchers and engineers to push the frontier of machine learning capabilities and deploying them for useful applications.
- Extensive software design and engineering experience
- Experience with designing and building large scale distributed systems, preferably for machine learning systems
- Knowledge and experience with cloud infrastructure
- Experience with machine learning frameworks and tools
Adept is an equal opportunity employer. We're excited about candidates who will raise the bar of our team, regardless of specific experiences -- we encourage applicants from a range of backgrounds to apply.