Software Engineer, ML Infrastructure
Nuro is hiring a Software Engineer, ML Infrastructure 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
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- Pay on this posting starts in line with the typical software engineer posting on Level.
- The posting mentions Kubernetes, Terraform and Docker among its tools and skills.
- Level classes it as a mid-level role.
- Nuro has 92 other open roles on Level.
AI in this role
Build and scale core ML infrastructure, resource provisioning pipelines, and workload orchestration platforms for autonomous driving systems.
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 is seeking a Software Engineer with expertise in large-scale infrastructure, workload orchestration, and data processing to join our ML Infrastructure team. In this role, you will focus on building and evolving the core platform that provides researchers and engineers with seamless access to compute and data resources. You will be responsible for executing the technical strategy for automated resource provisioning, high-performance workload scheduling, and efficient feature management to accelerate the Nuro Driver™ development lifecycle.
About the Work
You will build the foundation that powers Nuro’s model development from experimentation to production. Key responsibilities include:
- Resource Provisioning & IaC: Scaling automated infrastructure-as-code (IaC) pipelines to manage thousands of GPU/CPU nodes across diverse environments.
- Intelligent Scheduling: Designing and optimizing workload orchestration to maximize hardware utilization, minimize job wait times, and handle massive-scale distributed training.
- Data & ETL: Designing robust pipelines for the extraction and transformation of petabyte-scale sensor and telemetry data into ML-ready formats.
- Feature Management: Implementing robust feature caching and storage solutions to reduce redundant computations and ensure low-latency access to pre-computed features.
- Platform Abstraction: Contributing to a unified ML platform that abstracts complex cloud infrastructure for end-users.
About You
- Experience: 3+ years of professional experience in ML Infrastructure, Backend Platform Engineering, or Distributed Systems.
- Resource Provisioning: Deep familiarity with modern Infrastructure-as-Code and provisioning tools such as Terraform, Pulumi, or Crossplane.
- Workload Scheduling: Hands-on experience building or managing large-scale orchestrators for compute-heavy workloads (e.g., Kubernetes, KubeRay, Ray, Slurm, or Volcano).
- Distributed Data Processing: Proficiency in at least one distributed processing framework, such as Apache Spark or Apache Beam, for large-scale data extraction and transformation.
- Feature Management: Experience implementing or maintaining feature stores and caching layers (e.g., Feast, Hopsworks, or Redis-based custom caching).
- Systems Design: A strong understanding of distributed systems, networking, and storage bottlenecks in the context of high-performance computing.
Bonus Points
- Active contributor to open-source projects in the MLOps or Cloud-Native ecosystem (e.g., CNCF, Ray, or Kubeflow communities).
- Experience with high-performance storage systems (e.g., Lustre, Ceph, or specialized NVMe caching) for ML data loading.
- Knowledge of cost-optimization strategies for large-scale GPU clusters in public clouds (AWS, GCP, or Azure).
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 Infrastructure 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.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Pay
- This job starts at
- $160k
- Typical software engineer job
- $168k
This posting starts close to the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where infrastructure as code was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where machine learning infrastructure was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, Infrastructure As Code, Distributed Systems, ETL, and Machine Learning Infrastructure. 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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