NVIDIA is looking for a Senior MLOps Engineering Manager to lead the development and operation of large-scale data and ML pipelines for its Autonomous Driving organization in Santa Clara, CA. This role involves managing a technical engineering team focused on processing multimodal sensor data to support autonomous driving products. The ideal candidate will have a strong background in MLOps and engineering management, with a passion for customer-focused development. This position offers the opportunity to scale systems and teams in a fast-paced environment.

• Bachelor's or equivalent experience, Master's, or PhD in Computer Science, Electrical Engineering, or a closely 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 one or more domains such as 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.

• 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.
• Drive the development of robust, scalable, and observable MLOps systems that support model training and continuous evaluation.
• Partner closely with various teams to translate customer and program requirements into reliable production systems.
• Define technical vision, roadmap, success metrics, and operational benchmarks to ensure consistent execution.
• Champion customer-first thinking and ownership to deliver measurable value to internal and external AV customers.
• Provide technical guidance, mentorship, and career development for senior engineers and managers.
• Operate across multiple layers of the stack, including Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.

• Employees at NVIDIA are often offered comprehensive, day-one benefits—including medical, dental, and vision coverage with HSA support, life and disability insurance, an Employee Assistance Program, and a 401(k) with auto-enrollment. Many roles also have generous time off and holidays, donation matching (up to $10,000), and a wide menu of extras like FSAs, commuter benefits, legal and identity-theft protection, pet insurance, and wellness discounts. Optional programs can include student-loan and home-purchase support, plus family care resources and expert medical services.