Machine Learning Infra Engineer

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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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

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

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Infra Engineer San Francisco Office | OnSite ABOUT REDUCTO Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows. We've grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms. Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital. THE OPPORTUNITY As an ML Infra Engineer, you'll play a key role in building the inference and training frameworks that make it possible to deliver results at scale. You'll collaborate closely with our ML and Platform teams to scale training across nodes, develop faster and more efficient serving, and create observability across the stack. This is a high-impact role where you'll help define what high performance ML training and inference look like at Reducto. WHAT YOU'LL DO - Build, and maintain our training and inference stack with an emphasis for fast iteration on training + flexibility for exploring new methods and high performance in inference. - Develop benchmarks for both sets of stacks to identify bottlenecks. - Explore SOTA advances in training and inference and work to apply them. - Design systems for scaling model training across multi-node, multi-GPU environments with strong reliability and observability. - Scale

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