ML Engineer: Auto-Labeling & 3D Perception Systems

Lucidmotors; Southfield (MI); On-site; USD 150,000 - 230,000; Full time

Job summary

Lucid Motors is seeking a Machine Learning Engineer to develop scalable auto-labeling technologies for ADAS and autonomous driving. You will work at the intersection of ML, computer vision, spatial AI, and large-scale data infrastructure, building production-scale labeling for 2D/3D object detection, segmentation, and tracking.

The role emphasizes active learning, teacher-student workflows, and model-assisted labeling across camera and LiDAR data, with exposure to multimodal fusion, VLMs, and

Qualifications

• MS or PhD in Computer Science, Machine Learning, Robotics, Computer Vision, or a related field.
• Strong software-engineering skills in Python and/or C++, with PyTorch or equivalent deep-learning frameworks.
• Solid understanding of deep learning, computer vision, 3D geometry, multi-view reconstruction, sensor fusion, and transformer architectures.
• Experience developing detection, segmentation, tracking, depth, occupancy, or multimodal perception models.
• Experience building, evaluating, and deploying machine-learning systems using large-scale datasets.
• Ability to work independently and collaborate across research, software, data, and vehicle teams.

Responsibilities

• Design and deploy production-scale auto-labeling for 2D/3D object detection and segmentation.
• Develop auto-label validation, confidence scoring, consistency checks, and quality-monitoring frameworks.
• Create active-learning and human-in-the-loop workflows to improve label quality while reducing annotation effort.
• Build teacher-student and model-assisted labeling workflows for large-scale camera and LiDAR datasets.
• Develop advanced perception and fusion models using camera-based and LiDAR-based data.
• Develop multimodal fusion models combining camera, LiDAR, radar, GNSS/IMU, and map context.
• Improve temporal consistency, calibration robustness, and long-tail performance across diverse driving environments.
• Build end-to-end ML workflows from raw sensor ingestion to dataset delivery.
• Leverage Spatial AI and 3D Gaussian Splatting (3DGS) techniques for large-scale driving scenes.

Skills

Python

C++

PyTorch

Deep learning

Computer vision

Sensor fusion

Education

MS/PhD in CS/ML/Robotics/CV

Tools

Docker

Kubernetes

CI/CD

Job description

Lucid Motors is seeking a Machine Learning Engineer to develop scalable auto-labeling technologies for ADAS and autonomous driving. You will work at the intersection of ML, computer vision, spatial AI, and large-scale data infrastructure, building production-scale labeling for 2D/3D object detection, segmentation, and tracking.

The role emphasizes active learning, teacher-student workflows, and model-assisted labeling across camera and LiDAR data, with exposure to multimodal fusion, VLMs, and