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Machine Learning Infrastructure Tech Lead

Reducto· ML Infrastructure
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San Francisco, CAFull-timePosted 3mo ago

About the role

ML Infrastructure Tech Lead at Reducto, owning systems for high-performance model training and inference. Hands-on role focusing ~80% on building and optimizing infrastructure, with 20% on technical leadership and roadmap. Fully in-person in San Francisco.

Responsibilities

  • Own the technical direction and roadmap for Reducto's ML infrastructure.
  • Build and maintain our training and inference stack, balancing fast experimentation with high-performance production serving.
  • Optimize model serving at every layer, including kernels, runtimes, batching, scheduling, and distributed inference.
  • Design systems for reliable multi-node, multi-GPU training and inference.
  • Improve GPU utilization, latency, throughput, reliability, observability, and cost efficiency.
  • Develop benchmarks that identify bottlenecks and guide infrastructure investments.
  • Evaluate state-of-the-art advances in training and inference and apply the ones that matter.
  • Build the tooling and abstractions that help ML engineers move quickly from experiments to production.
  • Partner with ML and Platform engineers on architecture, capacity planning, and technical prioritization.
  • Raise the engineering bar through design reviews, mentorship, and hands-on technical leadership.

Qualifications

  • 5+ years of experience building production infrastructure, including significant ML systems experience.
  • Led complex technical projects from an ambiguous problem through production deployment.
  • Able to set direction and personally implement the hardest parts.
  • Strong Python and systems-engineering skills.
  • Understand performance characteristics of modern GPU training or inference workloads.
  • Comfortable with Kubernetes and distributed training or serving frameworks.
  • Ability to reason across low-level model performance and higher-level platform architecture.
  • High bar for quality, precision, and operational reliability.
  • Ability to operate in a fast-changing, high-growth environment.
  • Take full ownership from strategy through execution.

Skills

Required:PythonSystems EngineeringGPU Training/Inference

Benefits

  • Unlimited PTO, because great work requires recharging.
  • Daily Lunch, enjoy free lunch with teammates in the office.
  • Commuter Reimbursement, we’ll cover your transportation costs.
  • Comprehensive Insurance, medical, dental, and vision.
  • Health and Wellness Budget, up to $150 per month for wellness spending such as gym memberships or fitness classes.
  • Parental Leave, flexible scheduling that works for you and your family.
Last updated Sep 4, 2026. Interested? Apply on the company site.
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About Reducto

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