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Nuro

Software Engineer, Performance Tooling and Infrastructure

Mountain View, California (HQ)From $152kmidAdded 1 month ago

About this role

Nuro is seeking a Software Engineer to advance their Performance Simulation Platform, which integrates hardware and software for autonomous driving. The role focuses on developing and maintaining a benchmarking infrastructure that is vital for evaluating the performance of their AI technology across multiple systems.

What you'll do

  • Develop and maintain the job orchestration layer for performance benchmarks
  • Build monitoring and alerting systems for platform reliability
  • Design data pipelines for capturing performance metrics
  • Conduct statistical analysis and experimentation for performance results
  • Manage the benchmarking fleet's planning and hardware allocation
  • Collaborate cross-functionally with various engineering teams

What they're looking for

  • Strong programming skills
  • Experience with CI/CD pipelines
  • Knowledge of Kubernetes and cloud infrastructure
  • Proficiency in data analysis and visualization tools
  • Familiarity with Linux and system-level configurations
  • Understanding of performance metrics and benchmarking
  • Statistical analysis methodologies
  • Cross-team collaboration skills
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Nuro

Nuro builds autonomous vehicle platforms and fleet operations systems, with a focus on reliability, safety, and over-the-air update infrastructure. The company is hiring reliability engineers, software engineers, and operations specialists to improve vehicle hardware resilience, enhance system automation, and ensure fleet operational excellence.

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Likely interview questions

  • Walk us through how you would design a benchmarking infrastructure that reliably captures and validates real-time performance metrics across a distributed fleet of physical hardware before code reaches production.
  • Describe your experience building data pipelines at scale. How would you handle capturing fine-grained performance metrics from non-deterministic autonomy workloads and detecting regressions reliably?
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