Engineering Manager, Model Library

THE ROLE

You'll lead the Model Library team at Baseten — a small, high-ownership team focused on helping developers discover, evaluate, and select the right models for their specific use cases. This role is for a product-minded engineering manager who thrives in ambiguous, high-impact environments and can guide a team from early-stage product thinking through production-quality execution.

You'll stay technically grounded while driving the team's work across model discovery, evaluation frameworks, and the infrastructure that powers a best-in-class model library experience.

EXAMPLE INITIATIVES

• Model APIs for frontier models
• Model training built for production inference
• Introducing the Baseten Frontier Gateway

RESPONSIBILITIES

• Lead and grow a team of engineers, including hiring, mentorship, and career development.
• Own the Model Library product area end-to-end — from discovery and evaluation experiences to the APIs and tooling developers use to integrate models.
• Partner with product, ML, and cross-functional stakeholders to define scope, prioritize work, and communicate progress.
• Maintain a high technical bar through design doc reviews, code reviews, and hands-on architectural guidance.
• Drive product quality and reliability: define success metrics, establish feedback loops, and ensure a consistent, high-quality developer experience.
• Foster a culture of strong written communication, clear design thinking, and effective collaboration.

REQUIREMENTS

• Experience managing engineers building developer-facing products: APIs, SDKs, or developer tooling.
• Product intuition and technical judgment — able to balance speed, quality, and developer experience tradeoffs.
• Technically hands-on enough to review designs, debug issues, and earn the trust of a strong IC team.
• Strong written communication and cross-functional collaboration skills.
• Interest in AI/ML and the evolving model landscape; willingness to develop deep domain knowledge (ML expertise not required).
• Experience building or supporting self-serve workflows.

NICE TO HAVE

• Background as an IC in developer tooling, APIs, or ML infrastructure before moving into management.
• Experience with model evaluation, benchmarking, or comparison frameworks.
• Familiarity with inference platforms, LLM runtimes, or the model ecosystem (open-source and frontier).