Staff Machine Learning Engineer – (ADAS/Autonomous Driving)

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.

• 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.

• 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.

Salary Range: The compensation range for this position is specific to the locations listed below and is the range Lucid reasonably and in good faith expects to pay for the position taking into account the wide variety of factors that are considered in making compensation decisions, including job-related knowledge; skillset; experience, education and training; certifications; and other relevant business and organizational factors.

• 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.

• 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.

• 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.

• 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.

• 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.

$180,900—$265,320 USD

Compensation & Benefits: Lucid offers a comprehensive and competitive benefits package including medical, dental, and vision insurance; life and disability coverage; paid time off; paid holidays, paid sick leave; and a 401(k) retirement plan. Hourly/non-exempt employees accrue up to 120 hours paid time off, and salaried/exempt employee accrue up to 160 hours paid time off. Eligible employees may also participate in Lucid’s equity program and/or a discretionary annual cash incentive program.

Incentive and equity awards, if applicable, are determined based on individual performance, role scope, market considerations, and overall company results, in accordance with the terms of the applicable plans.

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To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to Lucid Motors. Lucid Motors is not responsible for any fees related to unsolicited resumes.

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.