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Nuro

Senior Software Engineer, ML Infrastructure Platform

Nuro is hiring a Senior Software Engineer, ML Infrastructure Platform in Mountain View, United States. It pays $194k-$291k a year and Level rates it ; you can apply on Nuro.

Level's read on this job

  • Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts 16% higher than the typical software engineer posting on Level.
  • The posting mentions Python, machine learning and distributed training among its tools and skills.
  • Level classes it as a senior role.
  • Nuro has 94 other open roles on Level.

AI in this role

Build and operate scalable ML infrastructure, distributed GPU training systems, and data pipelines for autonomous vehicles.

python
machine-learningdistributed-trainingmlopsdata-pipelines

Who We Are 

Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides.

Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.

With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.

Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors

About the Role

Nuro takes a machine-learning-first approach to autonomous driving, and the ML Infrastructure team builds and operates the infrastructure that makes that possible. We own the systems that train the models at the core of the Nuro Driver™ - from distributed GPU training and closed-loop reinforcement learning, to the workflows, orchestration, observability, and cost management that keep the fleet running efficiently.

Our work sits directly on the critical path of autonomy development. When a training run stalls, when a pipeline silently regresses, or when GPU utilization slips, it shows up in how fast the rest of the company can ship. We care as much about reliability and operational maturity as we do about raw scale.

About the Work

  • 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.

About You

  • BS, MS, or PhD in Computer Science, Electrical Engineering, or a closely related field, plus 3+ 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.

Bonus Points

  • Strong working knowledge of GCP.
  • Experience with building large-scale data generation pipelines.
  • Experience with Kubernetes-native orchestration for ML workloads.
  • Depth in GPU / distributed training internals, including NCCL and collective communication.
  • Familiarity with GPU and training observability tooling and using it to diagnose real bottlenecks.
  • A track record of driving down infrastructure cost while improving reliability.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $291,150 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.

How we rate this

Senior Software Engineer, ML Infrastructure Platform at Nuro rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningDistributed TrainingMLOpsData PipelinesPython

Also common in software engineer jobs at this level

Pay

This job starts at
$194k
Typical software engineer job
$167k

This posting starts 16% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where distributed training was part of your work. What did you do?
  3. Tell me about a project where mlops was part of your work. What did you do?
  4. Tell me about a project where data pipelines was part of your work. What did you do?
  5. Walk me through how you've used Python in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Machine learning, Distributed Training, MLOps, Data Pipelines, and Python. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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