Lead a machine learning engineering team designing Visual Language Action Models, Vision Language Models, and Large Language Models for autonomous driving and infotainment on Qualcomm's Snapdragon Ride platform. Optimize deep networks for accuracy-latency trade-offs on resource-constrained edge devices, focusing on low-level perception, end-to-end autonomous driving (L2/L3 ADAS), and multi-modal sensor fusion.… Drive cross-functional collaboration with automotive OEMs and internal Qualcomm teams while building a world-class AI/deep learning engineering organization. Requires 6–8+ years of systems engineering or machine learning experience (depending on degree level), with hands-on expertise in deep learning network design, quantization, and deployment on edge AI accelerators.
on-device-deployment jobs in San Diego
Qualcomm seeks an ML/computer vision engineer to develop and optimize AI-accelerated vision algorithms for edge devices (mobile, automotive, robotics, AR/VR). You will design algorithms for depth estimation, optical flow, video super-resolution, 3D reconstruction, and SLAM, then optimize deep learning models for resource-constrained SoCs.… The role spans algorithm research, model architecture design, performance profiling across memory/compute/power/bandwidth, and cross-functional collaboration with hardware and systems teams to ship production models for key customer segments.
Design, implement, and optimize video processing and computer vision algorithms for mobile and embedded platforms at scale, from concept through production deployment. Profile and optimize algorithm performance across memory, compute, power, and bandwidth constraints on SoCs with embedded accelerators.… Lead system and algorithm-level architecture, collaborate with cross-functional hardware and software teams, and provide technical mentorship to engineers across experience levels.