Sr/Staff Perception Machine Learning Engineer
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About this role
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.
We are looking for an experienced Perception Machine Learning Algorithm Engineer to join our ADAS/Autonomous Driving team. This position requires a highly skilled professional with a strong background in machine learning, computer vision, and perception algorithms, as well as solid programming expertise.
As a member of Lucid’s Perception team, you will research, design, implement, optimize, and deploy state-of-the-art machine learning models that advance perception algorithms for autonomous driving. You will conduct literature reviews, develop and modify models to enhance performance, and contribute to the deployment of these models in production vehicles.
Role and Responsibilities
• Develop and optimize perception algorithms for Level 2/2+/3 autonomous driving systems using camera, LiDAR and radar data.
• Design and implement cutting-edge deep learning algorithms for 2D/3D object detection, segmentation, tracking, and multi-task learning.
• Design, train, and evaluate machine learning or deep learning models for detecting vehicles, pedestrians, and other road users.
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