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Machine Learning Engineer

Sofia Garcia

Full-time · Job · Los_Angeles

About the role

As a fully async team spread across nine time zones, we believe great engineers don't need to sit in the same room to build reliable evaluation infrastructure. Our benchmark suites have grown faster than our ability to run them efficiently, and we need someone to rearchitect the training and inference pipelines behind them. You'll join a cross-functional squad with defined sprints, clear ownership, and weekly syncs with leadership, rebuilding our PyTorch and TensorFlow workloads to run reliably on Kubernetes at scale. This is core infrastructure work that every benchmark run depends on.

Responsibilities

  • Rearchitect training and inference pipelines for PyTorch and TensorFlow workloads
  • Containerize and orchestrate benchmark jobs on Kubernetes
  • Drive adoption of standardized ML infrastructure across research teams

Requirements

  • Strong production experience with PyTorch or TensorFlow at scale
  • Solid Docker and Kubernetes skills for orchestrating ML workloads
  • Comfort working in a fully distributed, async engineering team

Benefits

  • Fully remote, async-first culture
  • Flexible working hours across time zones
  • Equity and annual refresh grants

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Categories

AI & Machine Learning Engineers

Skills

python pytorch tensorflow docker kubernetes

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers

Skills

python pytorch tensorflow docker kubernetes

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