Senior ML/AI Engineer (Technical DevRel)

About the Position

We are looking for a Senior ML/AI Engineer with strong Technical DevRel capabilities to join the team in San Francisco full-time. The company is an AI startup working on small task-specific models, inference, and post-training. It has already built an open-source product with a growing developer community and is preparing to launch its cloud offering. The company works closely with model creators, database companies, infrastructure providers, and other technology partners to build integrations, technical demos, and practical AI use cases.

A formal DevRel title is not required. A strong ML/AI Engineer with deep technical expertise and an interest in speaking, teaching, creating demos, and working with the developer community may be a stronger fit than a traditional DevRel profile without sufficient ML/AI depth. You will work closely with the founder and contribute directly to both the product and its technical ecosystem.

Responsibilities

Your responsibilities will include:

• Contribute to the core product (approximately 25% of the role), staying hands-on and deeply involved enough to understand the technology and participate credibly in engineering discussions
• Drive highly technical Developer Relations activities (approximately 75% of the role)
• Work directly with external technology partners, including model creators, database companies, infrastructure providers, and other AI ecosystem companies
• Design and build technical demos, integrations, examples, and reference implementations with partners
• Develop practical use cases demonstrating how the company's technology can be integrated into real-world AI products and infrastructure
• Write technical articles, tutorials, documentation, and other developer-facing content
• Record technical demos and videos
• Lead or participate in technical webinars and workshops
• Speak at conferences, meetups, and other AI/developer events
• Participate in technical co-marketing initiatives with ecosystem partners
• Engage with the open-source and developer community from a deeply technical perspective
• Explain the company's technology and underlying ML concepts to engineers, developers, partners, and other technical audiences
• Bring feedback and insights from developers and partners back into the product and engineering process
• Represent the company credibly within the broader ML/AI engineering ecosystem

Requirements

• Senior-level ML/AI Engineering background with several years of hands-on experience in machine learning or advanced AI engineering
• Strong software engineering skills and ability to independently build production-quality solutions, prototypes, integrations, and demos
• Practical experience with production ML systems, rather than primarily consuming third-party LLM APIs
• Strong understanding of model inference and how ML models are deployed, served, optimized, and used in production environments
• Relevant experience in several areas such as small models, model inference, post-training, embeddings, vector search, information retrieval, reranking, recommendation/search systems, transformers, model serving, or ML infrastructure
• Ability to understand a complex ML product deeply enough to contribute to core engineering and credibly explain its architecture and technical value to other engineers
• Product-oriented engineering mindset and ability to translate ML technology into practical use cases
• Strong written and verbal English communication skills
• Genuine interest in working in a highly technical, public-facing role
• Comfort explaining complex technical concepts through demos, presentations, technical discussions, articles, webinars, workshops, or videos
• Existing US work authorization (mandatory, no visa sponsorship)
• Ideally already based in San Francisco / Bay Area, or willing and able to relocate quickly
• Willingness to work in a hybrid setup, approximately 2–3 days per week in person in San Francisco
• Interest in a long-term, full-time position

Nice to Have

• Previous experience in Technical DevRel, Developer Advocacy, or developer education
• Experience with GPU/inference infrastructure and inference optimization
• Experience with transformer architectures, model optimization, or post-training
• Strong background in search/retrieval systems, including embeddings, vector search, reranking, or hybrid retrieval
• Experience building developer-facing SDKs, APIs, integrations, examples, or technical tooling
• Open-source contributions or meaningful personal technical projects
• Active GitHub or another visible technical footprint
• Experience writing technical articles, tutorials, research-oriented content, or engineering blog posts
• Conference or meetup speaking experience
• Experience delivering technical webinars or workshops
• Experience producing technical video content
• Research experience combined with strong production engineering capabilities
• Previous experience in a fast-moving startup/product environment
• Experience collaborating directly with external engineering teams and technology partners

We Offer

• Employment type: direct hire, full-time employment with the company
• Engagement: long-term
• Location: San Francisco / Bay Area, USA
• Work format: hybrid, approximately 2–3 days per week in person, with the remaining time remote
• The founder is currently based in San Francisco; in-person work takes place in WeWork or a similar coworking environment
• Candidates already based in the Bay Area are strongly preferred
• For an exceptional candidate based elsewhere in the US, the company may be able to assist with relocation if the candidate can move quickly
• US work authorization: mandatory, no visa sponsorship
• Start: ASAP

About the Company

The company is an AI startup working on small task-specific models, inference, and post-training. It has already built an open-source product with a growing developer community and is preparing to launch its cloud offering. The company works closely with model creators, database companies, infrastructure providers, and other technology partners to build integrations, technical demos, and practical AI use cases.