Machine Learning Jobs at Nuro with Visa Sponsorship
Nuro's Machine Learning roles span autonomous vehicle perception, prediction, and planning systems, with a consistent track record of sponsoring international talent across multiple visa categories. If you're an ML engineer or researcher targeting a role in robotics and autonomy, Nuro actively supports the sponsorship process from offer through filing.
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Get Access To All JobsWho We Are
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.
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.
Who We Are
Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.
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.
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Get Access To All JobsTips for Finding Machine Learning Jobs at Nuro Jobs
Tailor your portfolio to autonomy-specific ML
Nuro's ML work centers on real-world robotics, not general-purpose AI products. Highlight experience with perception systems, sensor fusion, or reinforcement learning in physical environments. Generic NLP or recommendation system projects will carry less weight than applied robotics research.
Use Migrate Mate to find open ML roles at Nuro
Nuro posts Machine Learning positions across multiple platforms, but roles requiring sponsorship aren't always flagged clearly. Use Migrate Mate to filter specifically for Nuro ML jobs that align with your visa type, so you're targeting positions where your status is already expected.
Prepare for DOL prevailing wage scrutiny on ML titles
Job titles like 'Machine Learning Engineer' and 'Research Scientist' fall into different DOL wage levels. Confirm which level your role is classified at before signing, as mismatches between your title, duties, and wage level are a common source of H-1B RFEs.
Align your degree field to the specialty occupation standard
USCIS requires that your degree field directly relate to the ML role's duties. A degree in computer science, statistics, or electrical engineering maps cleanly. If yours is adjacent, prepare a credential evaluation that draws an explicit connection to the position's technical requirements.
Machine Learning at Nuro jobs are hiring across the US. Find yours.
Find Machine Learning at Nuro JobsFrequently Asked Questions
Does Nuro sponsor H-1B visas for Machine Learnings?
Yes, Nuro sponsors H-1B visas for Machine Learning roles. The company has an established pattern of filing H-1B petitions for technical positions across its autonomy and robotics engineering teams. If you're a cap-subject candidate, sponsorship is typically tied to the annual USCIS lottery cycle, with filings submitted in March for an October 1 start date.
How do I apply for Machine Learning jobs at Nuro?
Applications go through Nuro's careers portal. For international candidates, the most practical first step is filtering for roles where sponsorship is explicitly supported. Migrate Mate lets you browse Nuro's open Machine Learning positions filtered by visa type, so you can focus on roles that match your authorization status before applying directly through Nuro's site.
Which visa types does Nuro commonly use for Machine Learning roles?
Nuro supports several visa categories for Machine Learning hires, including H-1B, H-1B1 for Chilean and Singaporean nationals, TN for Canadian and Mexican candidates, F-1 OPT and CPT for students, J-1 for exchange visitors, and employment-based Green Card pathways including EB-2 and EB-3. The right category depends on your nationality, degree level, and where you are in your career.
What qualifications does Nuro expect for Machine Learning roles?
Nuro's ML positions typically require a graduate degree in computer science, statistics, electrical engineering, or a related quantitative field, along with hands-on experience in areas like perception, prediction modeling, or deep learning for physical systems. Research publications or prior work in robotics or autonomous vehicles strengthens an application significantly, particularly for senior or research-track roles.
How do I time my application around the H-1B filing calendar?
USCIS opens H-1B cap registrations in March each year, with approved petitions taking effect October 1. If you're targeting Nuro and currently on F-1 OPT, plan to have an offer in place before February to give your employer enough runway to register you. STEM OPT extensions provide up to 24 additional months of work authorization, which can bridge two full lottery cycles if needed.
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