Senior Manager, Machine Learning Ops Engineering - Automotive

We are seeking a Senior MLOps Engineering Manager to join our Autonomous Driving organization in Santa Clara, CA. This role offers an outstanding opportunity to lead the build, development, and operation of large-scale, end-to-end data and ML pipelines that power NVIDIA's autonomous driving products.

You will lead a highly technical engineering team responsible for building and operating cloud-scale pipelines that ingest, validate, process, and transform extensive volumes of multimodal sensor data,including camera, lidar, and radar,into high-quality training, evaluation, and validation datasets. These pipelines are foundational to NVIDIA's AV program and directly enable customer-facing autonomy features.

Responsibilities:

• Lead and grow a high-performing MLOps engineering group tasked with managing end-to-end data pipelines supporting NVIDIA's autonomous driving technology from levels L2 through L4.

• 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 that support model training, ground truth generation, and continuous evaluation at AV scale.

• Partner closely with perception, ML, data labeling, infrastructure, and product teams to translate customer and program requirements into reliable production systems.

• Define technical vision, roadmap, success metrics, and operational benchmarks, and ensure consistent execution against program achievements.

• Champion customer-first thinking and ownership, ensuring the systems your team builds directly deliver measurable value to internal and external AV customers.

• Balance hands-on technical depth with people leadership, 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 or equivalent experience, Master's, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).

• 10+ overall years of overall engineering experience, including crafting and coordinating production-grade distributed systems.

• 5+ years of engineering management experience, with a proven 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 crafting and operating end-to-end data or ML pipelines with high reliability, scale, and observability.

• Prior 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, capable of aligning collaborators and driving execution in a multi-functional organization.

• Demonstrated passion for ownership, accountability, and engineering that prioritizes customers.

Preferred Qualifications:

• Experience developing and leading AV-scale data platforms handling petabyte-scale sensor data.

• Strong background of 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.