Senior MLOps Engineer

NVIDIA is seeking a Senior MLOps Engineer to join its Autonomous Driving organization in Santa Clara, CA. The successful candidate will design and operate end-to-end data and ML pipelines for NVIDIA's autonomous driving products.

The role involves building and operating 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.

Responsibilities:

• 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.

Requirements:

• 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.

Benefits:

• Equity
• Benefits