Perception Machine Learning Engineer – ADAS
On-siteSouthfield, Michigan, United States
Southfield, Michigan, United StatesOn-siteFull TimeBachelors DegreeAutomotiveLarge
Full TimeBachelors DegreeLargeAutomotive
Job Summary
Develop and optimize perception algorithms for autonomous driving systems using camera and LiDAR data. Design and implement deep learning algorithms for 2D/3D object detection, segmentation, tracking, and multi-task learning, including BEV-based transformer models. Collaborate with cross-functional teams to ensure seamless integration and robust implementation, then test, release, and deploy these algorithms into Lucid production programs. Support validation and verification using prototype and pre-production vehicles while proposing innovative software to enhance future autonomous driving capabilities.
Required Qualifications
- 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
- Comfortable working with large codebases and debugging complex machine learning models
- 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
- 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
- Experience in Automotive/Autonomous Driving background
Desired Qualifications
- Advanced degrees are preferred
- Experience developing BEV transformer models for perception
- Proficiency in C++ with experience writing efficient, maintainable code
- Practical, hands-on approach to solving complex problems in autonomous driving
- Experience in testing and validating perception systems in real-world conditions
- Experience working in agile development teams
- Expertise in component and system integration, testing, and verification at the system and vehicle levels
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