Engineering Manager, Model Library

BaseTen Inc.

Job Overview

Location

San Francisco

Job Type

Full-time

Full Job Description

📋 Description

• Lead and grow a high-ownership engineering team focused on the Model Library product area, enabling developers to discover, evaluate, and select the right AI models for their use cases.
• Own the end-to-end product experience of the Model Library, including model discovery interfaces, evaluation frameworks, and the APIs and tooling developers use to integrate models into their applications.
• Partner closely with product, machine learning, and cross-functional teams to define product scope, prioritize initiatives, and communicate progress across stakeholders.
• Maintain a high technical bar through active participation in design doc reviews, code reviews, and providing hands-on architectural guidance to engineers.
• Drive product quality and reliability by defining success metrics, establishing feedback loops, and ensuring a consistent, production-grade developer experience.
• Foster a culture of strong written communication, clear design thinking, and effective collaboration across remote and in-office team members.
• Guide the team through ambiguous, high-impact product phases—from early-stage ideation to production deployment of model APIs, training infrastructure, and gateway services.
• Hire, mentor, and support the career development of engineers, creating growth paths and nurturing a high-trust, high-performance team environment.
• Stay technically grounded by reviewing system designs, debugging complex issues, and earning the trust of a team of individual contributors through demonstrated technical judgment.
• Build and scale self-serve workflows that empower developers to onboard, evaluate, and deploy models without needing direct support.
• Stay informed about the evolving AI/ML landscape, including open-source and frontier models, LLM runtimes, and inference platforms, to inform product direction and engineering priorities.
• Ensure the Model Library delivers a best-in-class experience that aligns with the needs of AI-first companies like Cursor, Notion, OpenEvidence, and Writer.
• Collaborate on initiatives such as Model APIs for frontier models, production-ready model training systems, and the Baseten Frontier Gateway.
• Balance tradeoffs between speed, quality, and developer experience while maintaining long-term scalability and reliability of the platform.
• Champion cross-functional alignment by translating technical constraints and opportunities into clear product strategy and roadmap priorities.

🎯 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.

🏖️ 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 (offices 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.

Skills & Technologies

Apache Spark

Onsite

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BaseTen Inc.

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About BaseTen Inc.

BaseTen provides a serverless, GPU-accelerated platform that lets machine-learning teams deploy, scale and monitor custom models behind autoscaling inference endpoints. The service abstracts infrastructure management, supports PyTorch, TensorFlow and Hugging Face artifacts, and offers built-in observability, A/B testing and fine-tuning. Customers integrate via REST or GraphQL APIs and pay only for compute used. Founded in 2019 and headquartered in San Francisco, BaseTen targets data scientists and product teams seeking production-grade ML serving without Kubernetes complexity.

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