Sr. Machine Learning Optimization Engineer - Autonomous Driving
Southfield, MI
Full Time Senior-level / Expert USD 134K - 184K
Lucid Motors
Lucid is the future of sustainable mobility, designing electric cars that further reimagines the driving experience.The Role
Lucid’s ADAS/Autonomous Driving division is seeking a highly skilled Machine Learning Optimization Engineer to enhance the efficiency of deep learning models for real-time inference. This role focuses on optimizing perception models for deployment on high-performance automotive hardware, leveraging advanced techniques such as quantization, pruning, and custom CUDA implementations.
Responsibilities
- Analyze ADAS/AD hardware to identify deep learning model optimization opportunities, working closely with cross-functional engineering teams.
- Lead the technical roadmap for deep learning inference optimization, implementing techniques such as quantization, compression, and pruning for current and future hardware platforms.
- Develop and integrate custom model optimizations using internal datasets and benchmarks, ensuring seamless deployment within existing training and inference pipelines.
- Debug and enhance deep learning deployment pipelines, optimizing preprocessing and postprocessing code for target devices using CUDA kernels to minimize latency.
- Conduct unit tests and validation to ensure the reliability, accuracy, and efficiency of optimized models.
- Collaborate with perception, software, and hardware teams to ensure optimized models meet real-time performance requirements.
Required Qualifications
- Strong experience in CUDA kernel development and TensorRT plugin optimization for deep learning inference.
- Proficiency in C/C++ programming, particularly for embedded systems and real-time applications.
- Solid understanding of deep learning model architectures, with hands-on experience optimizing models for deployment.
- Familiarity with automotive safety standards (e.g., ASPICE, ISO 26262) and their impact on software development.
- Bachelor's degree in Computer Engineering, Electrical Engineering, Automotive Engineering, Mechanical Engineering, or a related field.
- Minimum 3 years of professional experience or a Ph.D. for senior positions.
- Advanced degrees preferred.
Preferred Qualifications
- Experience working with automotive sensors (e.g., Camera, Radar, Lidar) in ADAS/AD applications.
- Familiarity with agile development methodologies and collaborative software development.
- Experience in system integration, testing, and verification at both the component and vehicle levels.
- Knowledge of Neural Architecture Search (NAS) techniques for optimizing deep learning model architectures.
By Submitting your application, you understand and agree that your personal data will be processed in accordance with our Candidate Privacy Notice. If you are a California resident, please refer to our California Candidate Privacy Notice.
To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to our careers alias or other Lucid Motors employees. Lucid Motors is not responsible for any fees related to unsolicited resumes.Tags: Agile Architecture Autonomous Driving CUDA Deep Learning Engineering Lidar Machine Learning Pipelines Privacy Radar TensorRT Testing
Perks/benefits: 401(k) matching Career development Competitive pay Equity / stock options Health care Insurance
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