Senior MLOps Manager

NVIDIA is developing AI and Accelerated Computing solutions for the Automotive industry. We are looking for a Senior MLOps Manager to lead data operations, ground truth (GT) production and delivery.

In this role, you will work alongside world‑class data engineering, data factory, outsource labeling and MLE teams on programs that directly impact NVIDIA’s autonomous driving stack. You will own the end‑to‑end GT operations lifecycle for WR/INDF, from requirements and planning through annotation, QA, and final delivery to model training and evaluation.

What You’ll Be Doing:

• Owning the GT production and delivery pipeline, ensuring datasets are delivered on time, at the right quality, and at the right scale for model training and validation.

• Defining GT requirements with Data Analyst and MLE teams, and translating them into clear labeling specs, QA specs, volumes, SLAs, and quality targets.

• Managing day‑to‑day GT operations across internal teams and external vendors, including task allocation, throughput tracking, and issue triage.

• Establishing and monitoring key operational metrics (throughput, quality, rework rate, audit pass rate, labeling cost), driving continuous improvement using data‑driven insights.

• Partnering with tooling and data infrastructure teams to improve labeling tools, QA workflows, and GT data pipelines, including opportunities to leverage AI agents to boost efficiency.

• Leading cross‑functional reviews and post‑mortems when GT issues are discovered, and driving root‑cause analysis and corrective actions.

What We Need to See:

• BS degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience).

• 10+ years of overall professional experience in data operations, labeling operations, ML data programs, or related fields, working with large‑scale data or ML‑driven products.

• 5+ years of direct leadership/management experience leading data operations, labeling teams, or cross‑functional GT programs (people management and/or end‑to‑end program ownership with defined KPIs and SLAs).

• Proven track record owning end‑to‑end data or GT operations, with clear examples of how you improved quality, efficiency, and reliability.

• Strong communication and stakeholder management skills, with experience working across engineering, ML, product, and vendor teams.

• Solid analytical skills and comfort working with metrics and dashboards to drive decisions.

Ways to Stand Out from the Crowd:

• Experience leading GT or labeling operations for autonomous driving, robotics, or other complex ML domains.

• Hands‑on familiarity with annotation tools, dataset management platforms, and data quality frameworks.

• Experience applying AI/agentic tooling to improve operations (e.g., auto‑labeling, active learning, agent‑assisted QA, or workflow automation).

• Prior experience managing external labeling vendors, including setting up SLAs, quality targets, and feedback loops.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward‑thinking and hardworking people in the world working for us. If you’re passionate about data, operations, and enabling world‑class AI models with high‑quality ground truth, we want to hear from you!