Staff Machine Learning Engineer - (ADAS/Autonomous Driving)
- Model Integration & Productization
- Deploy and integrate perception models (camera, LiDAR) into Lucid’s centralized software stack.
- Transition experimental components into production-ready modules with robust scheduling and diagnostics.
- Performance Optimization
- Optimize inference pipelines using CUDA, TensorRT, and mixed-precision techniques for real-time performance.
- Implement multithreaded scheduling and containerized deployments for automotive platforms.
- Pipeline Development & Automation
- Build CI/CD pipelines for nightly deployments, HIL verification, and KPI reporting.
- Automate data recording, evaluation frameworks, and regression testing.
- Cross-Functional Collaboration
- Work closely with ML researchers, software engineers, and OEM partners to ensure seamless integration.
- Support SDK development and customer-facing deliverables.
- System Diagnostics & Monitoring
- Implement runtime performance metrics, logging, and error reporting for perception stack reliability.
- BS/MS in Computer Science, Electrical Engineering, or related field.
- 7+ years of experience in software engineering for perception or autonomous systems.
- Strong proficiency in C++ and Python, with experience in ROS1/2, OpenCV, and GPU acceleration.
- Hands-on experience with ML frameworks (PyTorch) and inference optimization (TensorRT, CUDA).
- Expertise in containerization (Docker), CI/CD, and automated deployment pipelines.
- Proven ability to lead technical projects and collaborate across teams.
- Experience with automotive perception systems and ADAS software stacks.
- Familiarity with automotive safety standards (ISO 26262, ASPICE).
- Knowledge of multithreaded scheduling and real-time performance tuning.
- Background in SDK development and automotive customer integration.
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