Staff Machine Learning Engineer
@ Nuro

Mountain View, California, United States
$300,000
On Site
Full Time
Posted 24 days ago

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XXXXXXXXXX XXXXXXXXXXX XXXXXXXXX******* @nuro.ai
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Job Details

Who We Are

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro builds scalable driver technology combining cutting-edge AI with automotive-grade hardware.

About the Role

Join our ML Infrastructure team to optimize training runtime efficiency and input pipelines for model training, evaluation, and distillation workloads. This role accelerates the self-driving roadmap for commercial and personal mobility.

About the Work

  • Collaborate with ML teams to integrate optimized input pipelines.
  • Detect, diagnose, and resolve performance bottlenecks.
  • Optimize training performance and resource utilization.
  • Enhance input data pipelines for maximum accelerator utilization.
  • Champion reproducible and debuggable ML experimentation.

About You

  • B.S./M.S./Ph.D. in Computer Science, EE, or related field.
  • 4+ years of experience in ML infrastructure and distributed training.
  • Expertise in Python, distributed systems, and performance profiling.
  • Experience with ML compilers and model distillation techniques.

Bonus Points

  • Open source ML infra contributions or research publications.
  • Hands-on with Foundation Model infrastructure and advanced ML frameworks.

Compensation & Benefits

Base pay range: $235030 to $352290, with potential bonuses, equity, and competitive benefits.

Key skills/competency

  • ML Infrastructure
  • Distributed Systems
  • Python
  • Performance Profiling
  • Input Pipeline Optimization
  • ML Experimentation
  • Model Distillation
  • Debugging
  • C++
  • Scalability
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How to Get Hired at Nuro

🎯 Tips for Getting Hired

  • Research Nuro's culture: Study their mission, tech, and recent news.
  • Customize your resume: Highlight distributed systems and ML expertise.
  • Showcase hands-on projects: Detail performance optimization experience.
  • Prepare technical examples: Discuss profiling and debugging specifics.

📝 Interview Preparation Advice

Technical Preparation

Review distributed system architectures.
Practice Python performance optimization.
Study ML profiling and debugging methods.
Examine ML compilers and distillation techniques.

Behavioral Questions

Describe teamwork in high-pressure projects.
Explain how you debug complex systems.
Discuss handling project setbacks effectively.
Share your continuous learning examples.

Frequently Asked Questions