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Staff Machine Learning Engineer – (ADAS/Autonomous Driving)

Lucid Motors
CompanyLucid Motors
CategoryEngineering
LocationNewark
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted30 Jan 2025
Last verified3 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
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. The Role   We are seeking a  Staff Software Engineer  to lead the integration and deployment of advanced perception models into Lucid’s production ADAS and autonomous driving systems. This role focuses on  productizing ML models , ensuring robust performance on automotive-grade hardware, and building scalable pipelines for deployment and validation. You will collaborate with ML researchers, perception engineers, and hardware teams to deliver high-performance, safety-compliant solutions.   Key Responsibilities   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.   Required Qualifications   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.     Preferred Qualifications   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.   Back
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