Senior Software Engineer, Evaluation Flywheel — Autonomous Vehicles

NVIDIA; North Carolina; On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is building the future of autonomous driving and seeks a senior engineer to own the eval flywheel—turning road and simulation data into trusted, production-grade evaluation results. This hands-on leadership role shapes architecture, quality, and adoption across teams, from data pipelines to metric reporting.

We value independent execution, proactive communication, and 12+ years in software for autonomous systems or ML.

Qualifications

• 12+ years of software development experience, including autonomous vehicles, robotics, or large ML systems.
• Strong Python and data engineering skills for production-scale pipelines.
• Deep experience evaluating ML/robotic systems: metrics, datasets, and pipelines.
• BS or MS in Computer Science, Robotics, or a related field (or equivalent).

Responsibilities

• Own the eval flywheel architecture, quality, and adoption end-to-end.
• Define evaluation standards for golden datasets, versioning, and health.
• Build tooling for dataset pipelines and metric performance reporting.
• Collaborate with test engineering, behavior planning, and infrastructure teams.
• Work with AI model developers to speed evaluation iterations, including VLM-based approaches.

Skills

Python

Data engineering

ML systems

Technical leadership

Education

BS/MS in CS/Robotics

Job description

NVIDIA is building the future of autonomous driving, and evaluation is how we know the drive is getting better. Our AV Evaluation team owns the metrics, golden datasets, and closed-loop evaluation workflows that decide what ships in NVIDIA's self-driving stack — every model change runs through us. We are bringing frontier vision-language models and agentic techniques to evaluation at scale, and the early results are changing how our organization develops AI drivers!

We are looking for a senior engineer to own the engine that makes it all trustworthy: the eval flywheel. This is a hands‑on technical leadership role — the flywheel's architecture, quality, and adoption are owned end to end by this person, in code and in the room, not from a strategy document.

What You'll Be Doing

• Owning the eval flywheel's strategy and architecture: how road and simulation driving data becomes curated golden datasets, how metrics are measured against them (precision/recall), and how those results earn lasting trust with the teams that depend on them.
• Setting the standard for evaluation quality: golden dataset curation, versioning, and health; metric performance measurement; and release processes that keep results dependable as the system evolves.
• Building the tooling that helps our metric developers iterate quickly: self‑serve dataset pipelines, metric performance measurement, and quality reporting used every day by the team and our partners.
• Partnering with senior engineers and leaders across test engineering, behavior planning, and infrastructure — setting expectations, working through trade‑offs, and being the voice of evaluation quality in cross‑team decisions.
• Working directly with AI model developers so evaluation iteration speed becomes an advantage for the whole program, including our push into learned, VLM-based evaluation.

What We Need To See

• A track record of independent execution and technical leadership: finding the highest‑leverage problem, driving it across team boundaries, and delivering without waiting to be asked.
• Clear, proactive communication with engineers and senior leaders alike, at a fast pace.
• BS or MS in Computer Science, Robotics, or a related field (or equivalent experience).
• 12+ years building software, with significant time in autonomous vehicles, robotics, or large‑scale ML systems.
• Deep experience evaluating ML or robotic systems: metric design, ground‑truth and golden dataset curation, precision/recall methodology, and the data pipelines behind them.
• Strong Python and data engineering skills for production‑scale pipelines.

Ways To Stand Out From The Crowd

• Experience building an evaluation flywheel before — dataset curation, metric measurement, developer tooling — and the story of how it changed model development velocity.
• Closed‑loop simulation evaluation for autonomous driving, and the realism questions that come with it.
• Applying LLMs or VLMs to evaluation, or productionization the infrastructure behind them.
• A history of earning trust for metrics across skeptical partner teams.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

• You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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