Engineering Manager, Model Library

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products. 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). BENEFITS - Competitive compensation, including meaningful equity. - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).