Software Engineer - Model Developer Ecosystem

Baseten · Data AI · San Francisco, CA · EPD

Software Engineer focused on the model developer ecosystem, revamping the model library to help developers discover, evaluate, and select models. This role involves creating guides, evaluations, and educational content to navigate the specialized AI model landscape, operating at the intersection of technical depth, community building, and product thinking.

What you'd actually do

  1. Own the developer-facing narrative for the model library: guides, tutorials, demos, and reference content that help developers choose the right model for the job.
  2. Build and nurture both sides of the model ecosystem
  3. Develop evaluation frameworks and use-case-specific criteria that go beyond benchmark scores to reflect real-world developer needs.
  4. Create community programs, events, and education initiatives that establish Baseten as the destination for model discovery and selection.
  5. Collaborate cross-functionally with product, engineering, and marketing to translate developer feedback into product improvements.

Skills

Required

  • Hands-on experience as a developer — you can write code, read a diff, and engage credibly with engineers about technical tradeoffs.
  • Proven track record in developer relations, developer education, or technical content at a developer tools or infrastructure company.
  • Strong written and verbal communication skills; you can explain complex technical concepts clearly to a range of audiences.
  • Experience building or contributing to developer communities, ecosystems, or open source projects.
  • Genuine curiosity about the AI/ML model landscape — you follow model releases, understand capability tradeoffs, and care about practical applications over hype.
  • Comfort with ambiguity and a bias toward ownership; this is a new initiative and you'll help define what success looks like.

Nice to have

  • Experience with AI/ML infrastructure, inference platforms, or LLM tooling.
  • Familiarity with cost-optimization thinking in AI — evaluating when to use smaller, specialized, or fine-tuned models vs. frontier models.
  • Background supporting open source developer tooling or AI coding agents.
  • Experience running internal AI education programs for engineering organizations.
  • Prior work at a low-code, API-first, or model/data platform company.

What the JD emphasized

  • Proven track record in developer relations, developer education, or technical content at a developer tools or infrastructure company.
  • Genuine curiosity about the AI/ML model landscape — you follow model releases, understand capability tradeoffs, and care about practical applications over hype.