Software Engineer, ML Data Infrastructure

About the role

Nuro is building autonomous driving software for robotaxis and consumer vehicles. This role focuses on the infrastructure required to manage, process, and scale the data pipelines that power our machine learning models. You will own the design and execution of data infrastructure that directly supports the safety and reliability of our autonomous systems. The successful candidate will be responsible for ensuring that high-volume sensor data flows seamlessly from vehicles to training environments. You will partner closely with data scientists to translate model requirements into robust data storage and access patterns. This position demands a strong commitment to data integrity, system performance, and operational stability. You will play a key role in enabling rapid iteration on machine learning models through efficient data management. Your work will have a direct impact on the scalability of our data-driven development cycle.

Key facts

What you'll do

• Architect and maintain high-performance data pipelines for autonomous driving datasets, ensuring low latency and high throughput.
• Develop and deploy scalable tooling to optimize the efficiency of model training workflows and high-volume data ingestion processes.
• Partner with machine learning engineers to refine storage strategies and improve data retrieval mechanisms for complex sensor datasets.
• Implement rigorous data validation frameworks to guarantee data quality and pipeline reliability across the entire machine learning lifecycle.
• Design and evolve the architecture for data storage that supports the varied formats and large sizes of vehicle sensor inputs.
• Lead the implementation of monitoring solutions to track data health, pipeline performance, and system resource utilization.
• Collaborate with cross-functional teams to define standards for data management that align with product and research objectives.
• Optimize data processing workflows to reduce bottlenecks and accelerate the availability of training-ready datasets.
• Contribute to the development of automation that minimizes manual intervention in data handling and error resolution.
• Guide the adoption of best practices for data versioning, lineage tracking, and metadata management within the ML infrastructure.

Requirements

• Demonstrate professional experience in software engineering with a demonstrated focus on data infrastructure and large-scale data systems.
• Exhibit proficiency in designing and building scalable systems that can reliably handle large datasets and demanding workloads.
• Show a proven ability to work on-site at our Mountain View headquarters in a consistent and reliable manner.
• Hold authorization to work in the United States without requiring sponsorship for this position at this time.
• Bring strong problem-solving skills to diagnose complex issues in data flow and system performance.
• Apply solid understanding of data structures, algorithms, and system design principles to everyday engineering challenges.
• Commit to writing clean, maintainable, and well-documented code that supports long-term infrastructure goals.
• Communicate effectively with both technical and non-technical stakeholders to align on priorities and project outcomes.

Nice to have

• Hands-on experience with autonomous vehicle sensor data formats, processing pipelines, and associated challenges.
• Background in distributed systems architectures and cloud-based data processing technologies.
• Familiarity with machine learning infrastructure tools and data pipeline frameworks commonly used in production environments.
• Experience with containerization and orchestration platforms that support scalable data workloads.

Practical notes

• This position requires on-site presence at the Mountain View, California headquarters.
• Applicants must be authorized to work in the United States.
• By submitting an application for this role, you agree to the Nuro Privacy Policy.
• Full-time engagement is expected for this position based on current business needs.

This role is critical to the advancement of our autonomous driving capabilities and offers the opportunity to work on infrastructure that scales to meet the demands of real-world driving scenarios. You will be expected to take initiative in identifying improvements and driving projects from conception to production. The ideal candidate thrives in a fast-paced environment and is passionate about building systems that enable cutting-edge machine learning research. Success in this position will be measured by the reliability of the data pipelines, the efficiency of data access for models, and the ability to support rapid experimentation. If you are motivated by challenging infrastructure problems and want to contribute to the future of autonomous mobility, this position provides a direct path to make an impact.