Senior Manager, Machine Learning Ops Engineering - Automotive

NVIDIA•Us, CA

1d•Onsite

About The Position

NVIDIA is 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. We want a seasoned engineering leader with strong ownership and passion for customer‑focused development. This person will scale systems and teams in a fast paced, multi‑functional environment.

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.

Nice To Haves

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.

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.