Senior Manager, Machine Learning Ops Engineering - Automotive

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 272,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits plan

Competitive compensation

Job summary

NVIDIA Corporation in Santa Clara, CA seeks a Senior MLOps Engineering Manager to lead the end-to-end data and ML pipelines for autonomous driving. You will guide a technically skilled team building and operating cloud-scale pipelines that ingest, process, label, and validate multimodal sensor data into high-quality training and evaluation datasets.

The role combines ownership and leadership with hands-on depth across Python, C++, distributed systems, cloud infrastructure, CI/CD, and data

Qualifications

• 10+ years of engineering experience, including distributed systems.
• 5+ years in engineering management with leading teams.
• Strong MLOps, data pipelines, and cloud-based systems background.
• Proficiency in Python and C++, with performance-focused decisions.

Responsibilities

• Lead and grow an MLOps engineering group for end-to-end data pipelines.
• Own architecture, execution, and operational excellence of cloud-scale pipelines.
• Drive robust, observable MLOps systems for model training and evaluation.
• Collaborate with perception, ML, labeling, infrastructure, and product teams.

Skills

MLOps

Data pipelines

Distributed systems

Python

C++

Leadership

Education

Bachelor’s or higher in CS/EE

Master’s or PhD in CS/EE

Tools

CI/CD tooling

Cloud platforms (AWS/GCP/Azure)

Job description

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.**What You Will Be Doing:*** 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.**What We Need to See:*** 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.**Ways to Stand Out from the Crowd:*** 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.NVIDIA is widely considered one of the most sought-after employers in the technology industry. We offer highly competitive compensation along with an extensive benefits plan. Our work enables new universes of discovery—from artificial intelligence to autonomous vehicles—and brings once‐science‐fiction technologies into reality. If you are passionate about autonomous driving, scaling complex systems, and leading teams that deliver real customer impact, we would love to hear from you.Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.