MLOps Engineering Leader - Autonomous Driving Pipelines

NVIDIA Corporation; Santa Clara (CA); On-site; USD 272,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation in Santa Clara, CA is seeking a Senior MLOps Engineering Manager to lead end-to-end data pipelines for autonomous driving. You will direct a high‑caliber team building cloud‑native systems that ingest, process, validate, and transform multimodal sensor data into training and evaluation datasets.

This role blends hands-on technical leadership with people management, overseeing Python/C++ architectures, CI/CD, and scalable data platforms to deliver reliable production‑grade

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience).
• 10+ total years of engineering experience, including production-grade distributed systems.
• 5+ years of engineering management experience leading large-scale systems.
• Strong background in MLOps, data pipelines, and cloud-based distributed systems.
• Proficiency in Python and C++, with ability to guide performance-critical decisions.

Responsibilities

• Lead and grow a high-performing MLOps engineering group for end-to-end data pipelines across AV platforms.
• Own architecture, execution, and operational excellence of large-scale cloud-native pipelines for multimodal sensor data.
• Drive development of scalable MLOps systems supporting model training, ground truth generation, and evaluation at AV scale.
• Collaborate with perception, ML, data labeling, and infrastructure teams to translate requirements into production systems.
• Define technical vision, roadmap, and operational benchmarks, ensuring measurable value to customers.

Skills

Python

C++

Distributed systems

Cloud infrastructure

CI/CD

Data pipelines

Leadership

Communication

Education

Bachelor's degree in CS/EE or related

Job description

NVIDIA Corporation in Santa Clara, CA is seeking a Senior MLOps Engineering Manager to lead end-to-end data pipelines for autonomous driving. You will direct a high‑caliber team building cloud‑native systems that ingest, process, validate, and transform multimodal sensor data into training and evaluation datasets.

This role blends hands-on technical leadership with people management, overseeing Python/C++ architectures, CI/CD, and scalable data platforms to deliver reliable production‑grade