Staff Machine Learning Engineer – (ADAS/Autonomous Driving)

About Lucid At Lucid, we are creating exceptional mobility experiences through innovation to drive the world forward. Built on Lucid’s proprietary technology and software-defined vehicle architecture, our award-winning vehicles bring our “Compromise Nothing™” approach to the global automotive market. That means refusing to choose between performance and sustainability, design and engineering, ambition and integrity. In Lucid Air and Lucid Gravity, we have designed and built vehicles that have redefined their segments, combining exceptional range, performance, design, and expansive space in a single experience. We achieve this through deep vertical integration, with design, engineering, and production happening in-house across our global offices and manufacturing facilities. Our teams come from industries around the world, united by a shared commitment to excellence. By refusing to settle, you can help redefine what’s possible and shape the future of mobility. The Role The GeoAI team is building next-generation AI-powered data automation platforms for ADAS and autonomous driving. We are seeking a Staff Machine Learning Engineer to provide technical leadership and architect scalable auto-labeling technologies that transform fleet-collected sensor data into high-quality training datasets with minimal human intervention. This role sits at the intersection of machine learning, computer vision, spatial AI, and large-scale data infrastructure. You will set technical direction across perception models, 3D scene reconstruction, foundation models, and automated data-generation systems, while leading complex initiatives from research through production to accelerate autonomous-driving development. What You'll Do Lead Automated Data Labeling & Spatial AI • Architect scalable auto-labeling systems for perception tasks including detection, segmentation, tracking, occupancy, and scene understanding. • Drive active learning, human-in-the-loop, and model-assisted labeling strategies to improve data quality and efficiency. • Lead the application of Spatial AI and 3D Gaussian Splatting (3DGS) for scene reconstruction, label propagation, simulation, and synthetic data generation. Advance Perception & Multimodal AI • Lead development of camera-, LiDAR-, and multimodal perception models for detection, segmentation, tracking, depth estimation, and occupancy. • Define sensor fusion architectures leveraging camera, LiDAR, radar, GNSS/IMU, and map data. • Improve model robustness, generalization, and performance across diverse driving scenarios and edge cases. Apply Foundation Models at Scale • Define strategy for applying VLMs, VLAs, and multimodal foundation models to data automation, scene understanding, label generation, and edge-case discovery. • Build AI-powered workflows for dataset search, curation, validation, and quality assurance. • Evaluate emerging research and translate breakthroughs into production-ready capabilities. Scale & Productionize ML Systems • Architect distributed training, inference, and data-processing pipelines for fleet-scale datasets. • Establish standards for model quality, reliability, observability, scalability, and cost efficiency. • Partner across perception, mapping, simulation, autonomy, and platform teams to deliver end-to-end ML solutions. Provide Technical Leadership • Own the technical vision and roadmap for GeoAI, auto-labeling, and spatial AI initiatives. • Drive architecture reviews, technical strategy, and cross-functional alignment. • Mentor engineers, elevate engineering excellence, and build scalable platforms and best practices that accelerate team impact. Qualifications Required • MS or PhD in Computer Science, Machine Learning, Robotics, Computer Vision, or a related field, or equivalent practical experience. • 8+ years of relevant industry experience developing machine-learning, computer-vision, robotics, or large-scale data systems, including technical leadership of complex production initiatives. • Expert software-engineering skills in Python and/or C++, with deep hands-on experience using PyTorch or equivalent deep-learning frameworks. • Deep expertise in computer vision, 3D geometry, multi-view reconstruction, sensor fusion, transformer architectures, and modern perception systems. • Demonstrated experience architecting, evaluating, and deploying production ML systems using large-scale datasets and distributed compute. • Proven ability to define technical direction, lead ambiguous cross-team programs, influence architecture and roadmaps, mentor engineers, and communicate effectively across research, software, data, vehicle, and leadership teams. Preferred • Experience in autonomous driving, robotics, mapping, AR/VR, or spatial computing, with ownership of production systems or platform architecture. • Hands-on experience with 3DGS, NeRF, neural rendering, world models, or synthetic data generation at meaningful scale. • Experience architecting auto-labeling platforms, active-learning systems, human-in-the-loop workflows, or automated label-quality systems. • Experience leading camera-LiDAR fusion, depth estimation, 3D detection and tracking, or multimodal foundation-model initiatives. • Familiarity with VLMs, VLA models, SAM-family segmentation models, distributed computing, Docker, Kubernetes, CI/CD, cloud ML infrastructure, and production observability. At Lucid, we don’t just welcome diversity - we celebrate it! Lucid Motors is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, national or ethnic origin, age, religion, disability, sexual orientation, gender, gender identity and expression, marital status, and any other characteristic protected under applicable State or Federal laws and regulations. Salary Range: The compensation range for this position is specific to the locations listed below and is the range Lucid reasonably an