Senior Manager, Machine Learning Ops Engineering – Automotive

Details

NVIDIA is seeking a Senior MLOps Engineering Manager to join its Autonomous Driving organization in Santa Clara, California. The role involves leading the development and operation of large-scale, end-to-end data and machine learning pipelines that power NVIDIA's autonomous driving products. These cloud-scale pipelines ingest, validate, process, and transform extensive volumes of multimodal sensor data, including camera, lidar, and radar, into high-quality training, evaluation, and validation datasets.

The successful candidate will lead a highly technical engineering team, scale systems and teams in a fast-paced, multifunctional environment, and ensure that the systems developed deliver measurable value to internal and external autonomous vehicle customers.

Responsibilities

• Lead and grow a high-performing MLOps engineering group responsible for end-to-end data pipelines supporting NVIDIA's L2 through L4 autonomous driving technology.
• Own the architecture, execution, and operational excellence of large-scale, cloud-native pipelines for multimodal sensor data ingestion, processing, labeling, and validation.
• Drive the development of robust, scalable, and observable MLOps systems supporting model training, ground-truth generation, and continuous evaluation at autonomous vehicle scale.
• Partner with perception, machine learning, data labeling, infrastructure, and product teams to translate customer and program requirements into reliable production systems.
• Define the technical vision, roadmap, success metrics, and operational benchmarks, and ensure consistent execution against program objectives.
• Champion customer-first thinking and ownership, ensuring that the team's systems deliver measurable value to internal and external autonomous vehicle customers.
• Balance hands-on technical depth with people leadership by providing technical guidance, mentorship, and career development for senior engineers and managers.
• Operate across multiple layers of the stack, including Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.

Requirements

• Bachelor's degree or equivalent experience, master's degree, or PhD in Computer Science, Electrical Engineering, or a closely related field, or equivalent experience.
• 10 or more years of overall engineering experience, including developing and coordinating production-grade distributed systems.
• 5 or more years of engineering management experience, with a history of guiding teams delivering sophisticated, large-scale systems.
• Strong background in MLOps, data pipelines, and cloud-based distributed systems.
• Proficiency in Python and C++, with the ability to guide system-level and performance-critical build decisions.
• Experience developing and operating end-to-end data or machine learning pipelines with high reliability, scale, and observability.
• Experience in one or more of the following domains: autonomous vehicles, robotics, computer vision, deep learning, or GPU-accelerated computing.
• Excellent communication and leadership skills, with the ability to align collaborators and drive execution in a multifunctional organization.
• Demonstrated passion for ownership, accountability, and customer-focused engineering.

Preferred Qualifications

• Experience developing and leading autonomous-vehicle-scale data platforms handling petabyte-scale sensor data.
• Experience leading teams responsible for production MLOps or data infrastructure.
• Experience with automotive or robotic systems, including real-world sensor data pipelines.
• Background in distributed cloud systems, workflow orchestration, and large-scale CI/CD.
• Familiarity with 3D geometry, perception pipelines, or data generation based on simulated environments.

Compensation and Benefits

The base salary range is USD 272,000 to USD 431,250 per year. Actual base salary is determined by location, experience, and the pay of employees in similar positions. The role also includes eligibility for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. The company does not discriminate 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. NVIDIA uses AI tools in its recruiting processes. Applications will be accepted at least until March 27, 2026.