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San Francisco continues to be the global center for machine learning innovation. From foundational model training to real-time personalization, SF companies are pushing ML to its limits.

With the explosion of generative AI and LLM-based applications, ML engineers in San Francisco are in higher demand than ever.

Hiring here is extremely competitive. Companies must differentiate on mission, tooling, and the opportunity for impact.

Understand your competitors

Top SF ML employers include OpenAI, Google, Meta, and a wide range of AI-first startups spanning healthcare, SaaS, and robotics.

Engineers here typically work on large-scale infrastructure, ML ops, and advanced model development - often contributing to open-source frameworks or new algorithms.


 


 


 

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Hiring process

Most SF hiring loops involve 3-5 stages, including ML system design, algorithmic coding, and a project or case study.

Candidates expect modern ML stacks, supportive research culture, and clear paths to production.

Compensation differences

San Francisco ML engineers command some of the highest compensation globally, with equity playing a major role.

Companies hiring in SF often include research stipends, conference budgets, and flexible work environments to attract top talent.

Senior ML talent with a background in LLMs, deep learning, or applied AI in production is especially sought-after.

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Machine learning is only as powerful as the talent behind it.

At Harrison Clarke, we help you hire ML professionals who can turn data into decisions. Whether you're training foundation models or building applied AI tools, our team connects you with engineers, scientists, and research talent to bring your machine learning vision to life.

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