NVIDIA Corporation

Senior Manager, Machine Learning Ops Engineering - Automotive

NVIDIA Corporation$272K — $431K *
Manufacturing & Automotive
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or equivalent experience.
  • 10+ years of overall engineering experience, particularly in distributed systems.
  • 5+ years of engineering management experience with a focus on large-scale systems.
  • Strong foundation in MLOps, data pipelines, and cloud-based architectures.
  • Proficiency in Python and C++ for system-level decision-making.
  • Experience with reliable end-to-end data or ML pipelines.
  • Prior exposure to Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU computing.

Responsibilities

  • Lead and expand a high-performing MLOps engineering team for NVIDIA's AV technology.
  • Oversee architecture and operation of cloud-native multimodal data pipelines.
  • Develop scalable MLOps systems for model training and continuous evaluation.
  • Collaborate with cross-functional teams to align on customer and program needs.
  • Define and manage technical vision, roadmap, and success metrics for projects.
  • Prioritize customer-driven development to enhance internal and external systems.
  • Provide mentorship and technical guidance to senior engineers and managers.

Benefits

  • Extensive benefits plan including health coverage and retirement options.
  • Equity options for eligible employees.
  • Opportunities for career development and growth within a leading tech company.
Full 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.


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.

Applications for this job will be accepted at least until March 27, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ

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