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ReductoReductoSan Francisco, CA

Machine Learning Infra Engineer

Builds and maintains ML training and inference infrastructure, scales distributed workloads across GPU clusters, and develops tooling for observability and fast iteration. Requires strong Python, systems engineering, Kubernetes, and distributed training experience.

150k – 300k/yr
On-siteML Engineering

About the role

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 distributed training and inference workloads across large GPU clusters while improving utilization, reliability, and cost efficiency.
  • Build the tooling, abstractions, and observability that help ML engineers move faster from experiment to production.

You’ll Thrive Here If You

  • Hold yourself to a high bar for quality and precision.
  • Enjoy solving complex problems and building from first principles.
  • Have strong Python skills + a background in systems engineering.
  • Are comfortable with Kubernetes and distributed training frameworks.
  • Love getting your hands dirty with real-world implementation challenges.
  • Operate well in fast-changing, high-growth environments.
  • Collaborate effectively across technical and non-technical teams.
  • Take full ownership from strategy through execution.

Bonus points if you

  • Have experience at an early-stage or high-growth startup.
  • Have developed in open source training/inference stacks in a meaningful way.
  • Are excited to set up distributed inference across 100s-1000s of GPUs.
  • Care deeply about combining technical excellence with business impact.

Benefits at Reducto

  • Unlimited PTO
  • Lunch: Receive a free lunch to eat with your teammates daily at the office
  • Reimbursed Transportation
  • Insurance: Generous health insurance covering medical, dental, and vision
  • Health and Wellness Budget: Up to $150/mo reimbursement
  • Parental Leave

Skills

PythonKubernetesDistributed TrainingGPUMulti-Node TrainingInference FrameworksTraining FrameworksObservabilityBenchmarksSystems Engineering

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