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Software Engineer, ML Infrastructure Platform

Nuro· Offboard Infrastructure
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Mountain View, CA$160.4k - $240.5kFull-timePosted 2mo ago

About the role

ML Infrastructure engineering role focused on building and operating the systems that train models for the Nuro Driver, including distributed GPU training, orchestration, data pipelines, and reliability of training and release pipelines.

Responsibilities

  • Contribute to Nuro’s training infrastructure, spanning multi-generation accelerators, and multi-cluster scheduling and orchestration.
  • Design and operate large-scale data pipelines - batch and streaming ingestion, storage layout, and high-throughput data generation and storage.
  • Design and develop agentic-first ML workflows - data-to-training-to-evaluation pipelines that are introspectable, reproducible, and easy for autonomy teams to run and extend.
  • Own reliability for critical training and release pipelines: instrument them, define meaningful alerting, and build the on-call and incident-response practices that let the team catch regressions.

Qualifications

  • BS, MS, or PhD in Computer Science, Electrical Engineering, or a closely related field, plus 1+ years of relevant work experience.
  • Willingness to deep-dive into implementation and to raise the technical and operational standards of the broader engineering organization.
  • A demonstrated ownership mindset: you drive systems to operational maturity e.g. through monitoring, alerting, runbooks.
  • Strong proficiency in Python (and comfort with C++, Go or a similar systems language).
  • Hands-on experience running production infrastructure on Kubernetes.
  • Solid distributed-systems fundamentals and the ability to reason about performance, failure modes, and reliability across a complex system.

Skills

Required:PythonC++ or GoKubernetesDistributed systems

Benefits

  • annual performance bonus
  • equity
  • competitive benefits package
Last updated Aug 12, 2026. Interested? Apply on the company site.
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