Senior Manager, Machine Learning Ops Engineering - Automotive

Overview In this role you lead a high‑caliber MLOps team focused on building and operating large‑scale data and ML pipelines for NVIDIA’s autonomous driving program. You will own end‑to‑end cloud‑native pipelines handling multimodal sensor data to create robust training, evaluation, and validation datasets. Working closely with cross‑functional teams, you translate customer needs into reliable production systems and drive measurable value for internal and external AV customers. This is a hands‑on leadership role that blends technical depth with people leadership to scale complex systems and teams. Compensation / Benefitsequityextensive benefits plancompetitive compensationbase salary with rangeremote/inclusivity optionscareer growth opportunities ResponsibilitiesLead and grow a high‑performing MLOps engineering group supporting AV data pipelines from L2 to L4Own architecture, execution, and operations of large‑scale cloud‑native pipelines for multimodal data ingestion, processing, labeling, and validationDrive robust, observable MLOps systems enabling model training, ground truth generation, and continuous evaluation at AV scaleCollaborate with perception, ML, labeling, infrastructure, and product teams to turn requirements into reliable production systemsDefine technical vision, roadmap, success metrics, and operational benchmarks; drive execution against program goalsChampion customer‑first thinking ensuring systems deliver measurable value to AV customersBalance hands‑on technical depth with people leadership and career development for engineers and managersOperate across Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms Key requirements10+ years of engineering experience including production‑grade distributed systems5+ years of engineering management experienceStrong background in MLOps, data pipelines, and cloud‑based distributed systemsProficiency in Python and C++Experience building end‑to‑end data/ML pipelines with high reliability and observabilityExperience in Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPU‑accelerated computingExcellent communication and leadership skillsDemonstrated ownership and customer‑focused engineering mindsetstrong communicationleadership and mentorshipcross‑functional collaborationMLOpsdata pipelinescloud‑based distributed systems