Staff Machine Learning Engineer – Productization & Deployment (ADAS/Autonomous Driving)
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The role
Lead the integration and deployment of perception models (camera and LiDAR) into a centralized automotive software stack for production ADAS and autonomous driving systems.
Productize experimental components into production-ready modules with robust scheduling and diagnostics.
Optimize real-time inference pipelines using CUDA, TensorRT, and mixed-precision techniques for automotive-grade performance.
Implement multithreaded scheduling and containerized deployments to support automotive platforms.
Build CI/CD pipelines for nightly deployments, hardware-in-the-loop (HIL) verification, KPI reporting, automated data recording, evaluation frameworks, and regression testing.
Collaborate closely with ML researchers, perception engineers, and hardware teams to ensure seamless integration and to support SDK development and customer-facing deliverables, while maintaining runtime diagnostics and stack reliability.
Productize experimental components into production-ready modules with robust scheduling and diagnostics.
Optimize real-time inference pipelines using CUDA, TensorRT, and mixed-precision techniques for automotive-grade performance.
Implement multithreaded scheduling and containerized deployments to support automotive platforms.
Build CI/CD pipelines for nightly deployments, hardware-in-the-loop (HIL) verification, KPI reporting, automated data recording, evaluation frameworks, and regression testing.
Collaborate closely with ML researchers, perception engineers, and hardware teams to ensure seamless integration and to support SDK development and customer-facing deliverables, while maintaining runtime diagnostics and stack reliability.
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