Senior Manager, Machine Learning Ops Engineering - Automotive
$272k - $431k • US, CA, Santa Clara
Posted 12d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
On-site
Categories
Machine Learning Engineer
About the job
NVIDIA is seeking a Senior MLOps Engineering Manager to lead the build, development, and operation of large-scale, end-to-end data and ML pipelines that power the company's autonomous driving products. This role involves leading a highly technical engineering team responsible for building and operating cloud-scale pipelines that ingest, validate, process, and transform multimodal sensor data into high-quality training, evaluation, and validation datasets. These pipelines are foundational to the autonomous vehicle program and directly enable customer-facing autonomy features. The ideal candidate will be a seasoned engineering leader with strong ownership and a passion for customer-focused development, capable of scaling systems and teams in a fast-paced, multi-functional environment.
Responsibilities
- Lead and grow a high-performing MLOps engineering group managing end-to-end data pipelines for autonomous driving technology.
- 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 for model training, ground truth generation, and continuous evaluation.
- Partner with perception, ML, data labeling, infrastructure, and product teams to translate requirements into production systems.
- Define technical vision, roadmap, success metrics, and operational benchmarks.
- Champion customer-first thinking and ownership to ensure systems deliver measurable value.
- Provide technical guidance, mentorship, and career development for engineers and managers.
- Operate across multiple layers of the stack, including Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.
Requirements
- Bachelor's or equivalent experience, Master's, or PhD in Computer Science, Electrical Engineering, or a related field.
- 10+ 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 Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU-accelerated computing.
- Excellent communication and leadership skills.
- Demonstrated passion for ownership, accountability, and customer-prioritized engineering.
Benefits
- Highly competitive compensation
- Extensive benefits plan
- Eligibility for equity
- Eligibility for benefits