Senior Manager, Machine Learning Ops Engineering - Automotive
NVIDIA· Mgmt, Sys SW
Santa Clara, CA$272k - $431.3k + equityFull-timePosted 7mo ago
About the role
Senior MLOps Engineering Manager leading the build, development, and operation of large-scale data and ML pipelines for NVIDIA’s autonomous driving products. Owns cloud-native pipelines for multimodal sensor data ingestion, processing, labeling, validation, and supports model training, evaluation, and ground truth generation at AV scale. Combines technical leadership with people management and customer-focused delivery.
Responsibilities
- Lead and grow a high-performing MLOps engineering group tasked with end-to-end data pipelines supporting NVIDIA’s autonomous driving technology from levels L2 through L4.
- 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 that support model training, ground truth generation, and continuous evaluation at AV scale.
- Partner with perception, ML, data labeling, infrastructure, and product teams to translate customer and program requirements into reliable production systems.
- Define technical vision, roadmap, success metrics, and operational benchmarks, and ensure execution against program achievements.
- Champion customer-first thinking and ownership, delivering measurable value to internal and external AV customers.
- Balance hands-on technical depth with people leadership, providing guidance, mentorship, and career development for senior engineers and managers.
- Operate across Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.
Qualifications
- Bachelor’s or equivalent experience, Master’s, or PhD in Computer Science, Electrical Engineering, or related field (or equivalent).
- 10+ overall years of engineering experience, including crafting and coordinating production-grade distributed systems.
- 5+ years of engineering management experience delivering large-scale systems.
- Strong background in MLOps, data pipelines, and cloud-based distributed systems.
- Proficiency in Python and C++, with ability to guide system-level and performance-critical decisions.
- Experience crafting and operating end-to-end data or ML pipelines with high reliability, scale, and observability.
- Experience in Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU-accelerated computing.
- Excellent communication and leadership skills, capable of aligning collaborators and driving execution in a multi-functional organization.
- Demonstrated ownership, accountability, and customer-focused engineering mindset.
Skills
Required:MLOpsPythonC++Distributed SystemsCloud InfrastructureData PipelinesLeadership / People ManagementCommunication
Benefits
- Competitive compensation
- Extensive benefits plan
Last updated Oct 9, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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