Staff Machine Learning Engineer – (ADAS/Autonomous Driving)
Lucid Motors
| Company | Lucid Motors |
| Category | Engineering |
| Location | Newark |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 30 Jan 2025 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (greenhouse) |
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.
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