Senior/Staff Software Engineer - Machine Learning & System Optimization
Core
Orchestrate system capacity and optimize multi-modality foundation models for autonomous vehicle perception stacks.
Role type
Senior/Staff IC Machine Learning and System Optimization Engineer
Builds
Production-ready, efficient inference pipelines for on-vehicle SoCs
Domain
Autonomous driving / Edge AI / System Optimization
Deliverable
production ML models
Required skills
System capacity allocation, Model quantization (PTQ, QAT), Mixed-precision inference, Custom CUDA kernel development, Low-latency C++ programming, TensorRT pipeline architecture, Multi-modal sensor fusion optimization
Preferred skills
High-performance robotics experience, SOTA autonomous driving perception algorithms (BEV, 3D Occupancy), End-to-end autonomous driving paradigms (VLM/VLA)
Technologies
CUDA, C++ (14/17/20), Python, TensorRT, PTQ, QAT, LoRA, QLoRA, INT8, FP8, BF16
Responsibilities
Allocate and distribute system resources (CPU/GPU/interconnect) to inference engines, Spearhead cross-cutting initiatives for better compute utilization via model sharing/fusing, Optimize large-scale models using quantization and pruning, Architect and implement model conversion/compilation pipelines, Write production-level low-latency C++ and CUDA code
Seniority
Senior/Staff, hands-on IC
