Applied Machine Learning Engineer
Inference, San Francisco
The role
You will be responsible for building and improving the core ML systems that power our custom model training platform, while also applying these systems directly for customers. Your role sits at the intersection of applied research and production engineering. You'll lead projects from data intake to trained model, building the infrastructure and tooling along the way.
Your north star is model quality at scale, measured by how well our custom models match frontier performance, how efficiently we can train and serve them, and how smoothly we can deliver results to our customers. You'll own the full training lifecycle: processing data, creating dashboards for visibility, training models using our frameworks, running evaluations, and shipping results. This role reports directly to the founding team. You'll have the autonomy, a large compute budget / GPU reservation, and technical support to push the boundaries of what's possible in custom model training.
What you will do
- Lead projects from from data intake through the full training pipeline, including processing, cleaning, and preparing datasets for model training