Lucid Motors is looking to advance perception algorithms for autonomous driving by developing and optimizing state-of-the-art machine learning models.
Requirements
- Strong theoretical foundations and expertise in deep learning algorithms, including object detection, tracking, and segmentation
- Proficient in Python with a focus on clean, efficient, and scalable software development
- Experience with PyTorch or other ML frameworks (e.g., TensorFlow, MXNet)
- Ability to design and construct evaluation pipelines to unit-test ML models under diverse conditions and environments
- Experience developing BEV transformer models for perception
- Proficiency in C++ with experience writing efficient, maintainable code
- Expertise in component and system integration, testing, and verification at the system and vehicle levels
Responsibilities
- Develop and optimize perception algorithms for Level 2/3 autonomous driving systems using camera and LiDAR data
- Design and implement cutting-edge deep learning algorithms for 2D/3D object detection, segmentation, tracking, and multi-task learning
- Research and integrate BEV-based transformer models for perception tasks
- Collaborate with cross-functional teams to ensure seamless integration and robust implementation
- Test, release, and deploy perception algorithms into Lucid production programs
- Support the validation and verification of perception algorithms using prototype and pre-production vehicles
- Propose innovative software algorithms to enhance future autonomous driving capabilities
Other
- Excellent communication skills and a strong team player
- Bachelor’s degree in Computer Engineering, Electrical Engineering, Automotive Engineering, Mechanical Engineering, or a related field
- Minimum of 3 years of relevant work experience, or a Ph.D. in a related field for a senior position
- Advanced degrees are preferred
- Experience working in agile development teams
- Practical, hands-on approach to solving complex problems in autonomous driving
