Want to build the data infrastructure that powers autonomous driving at scale? NVIDIA is seeking a Senior MLOps Engineer to join our Autonomous Driving organization in Santa Clara, CA. This individual contributor will design and operate end‑to‑end data and ML pipelines for NVIDIA’s autonomous driving products!
The role builds and operates cloud pipelines that ingest, validate, process, and transform multimodal sensor data from camera, lidar, and radar into training, evaluation, and validation datasets. These pipelines enable NVIDIA’s AV program and customer‑facing autonomy features. Bring ownership, customer focus, and engineering judgment to scale systems and solve problems across teams.
What You Will Be Doing:
Design, build, and operate data pipelines supporting NVIDIA’s autonomous driving technology from levels L2 through L4.
Own architecture, implementation, and operations for cloud pipelines that ingest, process, label, and validate sensor data.
Build observable MLOps systems for model training, ground truth generation, and continuous evaluation at AV scale.
Translate customer and program requirements into production systems with perception, ML, data labeling, infrastructure, and product teams.
Set technical direction, roadmaps, metrics, and operational benchmarks; deliver against program milestones.
Build systems that deliver measurable value to internal and external AV customers.
Contribute through design reviews, implementation, debugging, code reviews, and mentorship.
Work across 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).
8+ years of engineering experience designing and delivering production distributed systems.
Technical leadership as a senior individual contributor delivering large‑scale systems.
Experience with MLOps, data pipelines, and cloud distributed systems.
Proficiency in Python and C++ for system‑level and performance‑critical implementation.
Experience operating end‑to‑end data or ML pipelines for 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.
Communication skills that align collaborators and drive execution across functions.
A record of ownership, accountability, and customer‑focused engineering.
Ways to Stand Out from the Crowd:
Experience with AV data platforms handling petabyte‑scale sensor data.
Hands‑on contributions to 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.
You will also be eligible for equity and benefits.
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.Skills Required
- Bachelor's degree or equivalent experience in Computer Science, Electrical Engineering, or related field
- 8+ years engineering experience designing and delivering production distributed systems
- Technical leadership as a senior individual contributor delivering large-scale systems
- Experience with MLOps, data pipelines, and cloud distributed systems
- Proficiency in Python
- Proficiency in C++
- Experience operating end-to-end data or ML pipelines for reliability, scale, and observability
- Prior experience in Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU-accelerated computing
- Strong communication skills to align collaborators and drive execution
- Record of ownership, accountability, and customer-focused engineering
- Experience with AV data platforms handling petabyte-scale sensor data
- Hands-on contributions to production MLOps or data infrastructure
- Experience with automotive or robotic systems and real-world sensor data pipelines
- Background in distributed cloud systems, workflow orchestration, and large-scale CI/CD
- Familiarity with 3D geometry, perception pipelines, or simulated data generation
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
