ML Performance Optimization Engineer
Core
Optimizing AI models and improving system performance to ensure autonomous driving models operate efficiently and reliably in vehicle environments.
Role type
ML Performance Optimization Engineer
Builds
Optimized AI models and performance analysis tools for autonomous driving systems
Domain
Autonomous Driving / Embedded Systems
Deliverable
production ML models
Required skills
Low-level performance optimization, C/C++, Python, Shell scripting, Linux/QNX/RTOS development, System profiling, Deep learning systems understanding
Preferred skills
ML workload optimization, Linear algebra optimization, Image processing/CV/Robotics optimization, CUDA/MKL/SIMD/NEON, NVIDIA vehicle platform experience, Autonomous driving AI model optimization
Technologies
GPU, NPU, CPU, CUDA, MKL, SIMD, NEON, Linux, QNX, RTOS, NVIDIA platforms
Responsibilities
Optimize deep learning models using GPU/NPU acceleration, Validate deep learning model performance and conduct system profiling, Analyze and optimize CPU, GPU, and neural network accelerator performance, Develop and automate system performance analysis tools and evaluation metrics, Support deployment and runtime optimization of AI models in vehicle environments
Seniority
Mid-Senior, hands-on IC
