Level

NuroPosted 4mo ago

L4

Senior/Staff Software Engineer, ML Data Infrastructure

Senior/Staff Software Engineer, ML Data Infrastructure at Nuro scores 85 out of 100 on AI centrality, which makes it a Level 4 role on this board.

Mountain View, California (HQ)lead$194k-$352k

AI in this role

ai-data-labeling

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 technology. In an ML-first system, the overall system performance depends heavily on the quantity and diversity of its training and evaluation data. 

The team plays a crucial role in the advancement of autonomous driving systems by creating a scalable and reliable data infrastructure. This infrastructure is designed to produce training and evaluation data derived from both on-road collected logs and simulation logs. Additionally, the team collaborates closely with system engineers to thoroughly validate the autonomous driving system before its deployment.

About the Work

  • Design and develop unified, introspectable, large-scale batch and streaming data pipelines that can ingest and process data across a wide range of use cases relevant to evaluation.
  • Create and implement a storage system capable of accommodating both the large volume and diverse range of evaluation and performance metrics.
  • Construct intuitive dashboards and reports to present evaluation results, facilitating straightforward comparisons that highlight both improvements and regressions of the ML components and the overall system.
  • Develop and maintain continuous testing and monitoring systems to guarantee the integrity and resilience of our data and associated data pipelines.
  • Develop data mining tools with applied ML techniques to support data discovery needs from Autonomy including Perception, Behavior, and Mapping
  • Develop data annotation tools to support first-party and third-party labeling workforce to provide high fidelity perception, mapping, and driving trajectory labels
  • Scale data annotation labels with applied State-of-the-art ML techniques

About You

  • You have a degree in BS, MS.c or Ph.D, plus 4 years of relevant work experience
  • Strong proficiency in Python or similar languages
  • Domain experience: Experience working with large-scale data and building scalable & reliable systems/data pipelines; ability to understand and design complex systems
  • Engineering leadership: Experience setting team or project product and technical vision, timelines, and prioritization; being a Technical Lead, mentoring and support junior engineers
  • Technical excellence: Ability and willingness to deep dive into implementation, driving technical standards and best practices across broader software organization
  • A bachelor's degree in Computer Science, Electrical Engineering, or a closely related field

Bonus Points 

  • Strong proficiency in C++ or other high-performance low-level languages
  • Strong knowledge of GCP, GCS, BigQuery, or PostgreSQL
  • Knowledge of data engineering, and its tooling and best practices
  • Knowledge of batch and streaming data processing, warehousing, and analytics solutions
  • Experience working with large-scale distributed data systems
  • Experience with system & framework design
  • Experience with data workflow orchestration platforms

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $193,930 and $352,290 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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI Data Labeling

Questions you could be asked

  1. How do you keep labeling instructions consistent across a large annotation team?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: AI Data Labeling. 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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