Engineering Manager AI & Data

Job Title: Engineering Manager AI & Data Overview We are looking for an Engineering Manager to lead AI and data engineering teams building core systems for autonomous driving. This role focuses on driving a team developing machine learning models, large-scale data pipelines, and infrastructure powering perception, prediction and decision-making systems in self-driving vehicles. You will balance technical leadership with team development, ensuring safe, scalable, and high-performance solutions. Key Responsibilities Lead and grow a multidisciplinary team of ML engineers, data engineers, and software engineers Drive development of AI models for perception (e.g., object detection, tracking), prediction, and sensor fusion Oversee large-scale data pipelines for ingesting, labeling, training, and validation of driving datasets Define and enforce best practices for ML lifecycle management (training, evaluation, deployment, monitoring) Guide architecture for distributed training systems and real-time inference pipelines Manage project timelines, prioritization, and cross-functional dependencies Establish safety, reliability, and validation standards aligned with autonomous driving requirements Stay current with advancements in AI, computer vision, and autonomous systems Build, Train & Manage High Performance Teams Required Qualifications Bachelor s or Master s degree in Computer Science, Electrical Engineering, Robotics, or related field Overall 12+ years of exp with 2+ years of experience in engg manager roles in a software product development background3+ years of experience managing engineering or ML teams Good Understanding of AI, ML & CV Solid understanding of data pipelines, distributed systems, and cloud infrastructure Experience with large-scale datasets and model training workflows Preferred Qualifications Experience in autonomous driving, robotics, or ADAS systems Familiarity with sensor modalities (LiDAR, radar, cameras) and sensor fusion techniques Knowledge of simulation environments and synthetic data generation Experience with real-time systems and edge deployment constraints Understanding of safety standards such as ISO 26262 Key Skills Leadership in ML/AI engineering teams Good understanding of computer vision and deep learning systems Data-driven decision making Cross-functional collaboration (hardware, simulation, product) Understanding of Scalable system architecture and MLOps practices Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.