Machine Learning Scientist

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Relocation assistance

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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Deadline

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About this role

Machine Learning Scientist San Francisco | OnSite About Us Relace is building the models and infrastructure that code agents reach for. We power the fastest model on OpenRouter (10,000 tok/s) and deliver optimized small language models designed for retrieval, application, and core code generation functions. Our technology supports some of the world's fastest-moving companies - including Lovable, Figma, and Vercel - as they deploy and scale code generation to hundreds of millions of users. We recently raised our Series A from a16z, and we're growing quickly. Our team is made up of mathematicians, physicists, and computer scientists who are deeply passionate about their craft. If you thrive on ambitious technical problems, care about elegant systems design, and want to build the foundation of how code gets written at scale, this is the place for you. THE ROLE We're looking for a Machine Learning Scientist to push the limits of small, high-performance language models. This is a deeply technical role focused on advancing the capabilities of our models for retrieval, application, and code generation. The ideal candidate has a strong background in ML research and engineering, is comfortable working with both theory and production systems, and thrives in an environment where ideas turn into deployed infrastructure fast. This person should be excited to work on training methodology, optimization, evaluation, and model architecture at scale - and collaborate directly with infrastructure and product teams to get breakthroughs into production quickly. This role is best suited for someone who loves both mathematical elegance

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