NVIDIA
Senior Manager, Machine Learning Ops Engineering - Automotive
$272K–$431K
US, CA, Santa Clara · Manager · Full-time · Posted Oct 7, 2026
- Experience
- 10+ years of engineering experience and 5+ years of engineering management experience.
- Education
- Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).
About the job
Leads a technical team building and operating large-scale MLOps pipelines that turn autonomous-vehicle sensor data into datasets and systems for training, evaluation, and validation.
What you'll do
- Lead and develop an MLOps engineering group supporting autonomous-driving technology from L2 through L4.
- Own the architecture and operation of cloud-native pipelines for multimodal sensor data ingestion, processing, labeling, and validation.
- Set technical direction and operational goals, partner across teams, and mentor engineers and managers.
What they ask for
- Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).
- 10+ years of engineering experience, including crafting and coordinating production-grade distributed systems.
- 5+ years of engineering management experience.
- Strong MLOps, data-pipeline, and cloud-based distributed-systems background; proficiency in Python and C++.
Nice to have
- Experience with petabyte-scale AV sensor data platforms or production MLOps/data infrastructure.
- Experience in automotive or robotics systems, distributed cloud systems, workflow orchestration, large-scale CI/CD, 3D geometry, perception, or simulated data generation.
Pay
272,000 USD - 431,250 USD base salary
Tools
Python, C++, distributed systems, cloud infrastructure, CI/CD
AI focus
Builds MLOps pipelines supporting autonomous-driving model training, ground truth generation, and continuous evaluation.
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