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Nuro

Software Engineer, ML Inference Platform

Nuro is hiring a Software Engineer, ML Inference Platform in Mountain View, United States. It pays $160k-$241k a year and Level rates it ; you can apply on Nuro.

Level's read on this job

  • On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
  • The listed pay starts close to the typical software engineer posting on Level.
  • Tools and skills the posting cites include Python, C and mlops.
  • Level classifies it as a mid-level role.
  • Level lists 92 other open roles at Nuro.

AI in this role

Build and scale the core machine learning infrastructure and inference platforms for autonomous driving systems.

PythonC
mlopsmachine-learning-infrastructuremodel-deploymentinference-optimization

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

The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots!

About the Work

  • Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models.
  • Develop and maintain continuous testing and monitoring systems for core ML infrastructure components.
  • Develop observability to track ML model lifecycles from data generation to on-road validation.
  • Maintain an in-house ML inference platform to serve large language models efficiently.
  • Maintain an in-house ML compiler platform to compile, deploy, and validate Nuro autonomy models to various hardware platforms.

About You

  • You have a degree in BS, MS.c or Ph.D with 1+ years of relevant experience
  • Strong proficiency in Python or similar languages. Familiarity with c++.
  • Technical excellence: Develop with a high standard for performance, scalability, and code quality.
  • Domain experience: Experience working with ML pipelines; ability to understand and design complex distributed systems
  • Independence and productivity: Ability and willingness to dive into unfamiliar territory, learn fast, and improve complex systems.

Bonus Points

  • Strong proficiency in C++ or other high-performance low-level languages
  • Experience working with large-scale distributed systems
  • Experience with system & framework design
  • Experience with data workflow orchestration platforms
  • Experience with ML compilers

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $160,360 and $240,540 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

Software Engineer, ML Inference 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

MLOpsMachine Learning InfrastructureModel DeploymentInference OptimizationPythonC

Also common in software engineer jobs at this level

Pay

This job starts at
$160k
Typical software engineer job
$167k

This posting starts close to the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Tell me about a project where mlops was part of your work. What did you do?
  2. Tell me about a project where machine learning infrastructure was part of your work. What did you do?
  3. Tell me about a project where model deployment was part of your work. What did you do?
  4. Tell me about a project where inference optimization 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: MLOps, Machine Learning Infrastructure, Model Deployment, Inference Optimization, 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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