Senior Manager, Machine Learning Ops Engineering - Automotive

NVIDIA is hiring a Senior Manager, Machine Learning Ops Engineering - Automotive in Santa Clara, United States. It pays $272k-$431k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include MLOps, AI data labeling and computer vision.
Level classifies it as a senior role.
Level lists 2,600+ other open roles at NVIDIA.

AI in this role

ml-opsai-data-labelingcomputer-vision

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.

#AutonomousVehicles

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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.

How we rate this

Senior Manager, Machine Learning Ops Engineering - Automotive at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Manager, Machine Learning Ops Engineering - Automotive is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $272k-$431k a year.
The role is based in US, CA, Santa Clara.
The job was posted on September 10, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI Data LabelingComputer vision

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How do you keep labeling instructions consistent across a large annotation team?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ML Ops, AI Data Labeling, and Computer vision. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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