distillation jobs in San Diego

AI Research Scientist role focused on developing and optimizing large language models for on-device deployment on smartphones, IoT, and automotive systems. Responsibilities include researching and prototyping model compression, quantization, pruning, distillation, and inference optimization techniques.…See more The role involves collaboration with silicon, software, and product teams to design experiments, benchmark models, and translate research into production-ready solutions for 5G and edge AI applications.

Qualcomm seeks a Computer Vision Engineer to develop machine learning algorithms for optical flow, depth estimation, visual tracking, SLAM, and 3D reconstruction on Snapdragon platforms. You will own end-to-end algorithm development—from training state-of-the-art neural networks and managing large datasets to optimizing and deploying models on-device for real-time performance.…See more The role requires deep expertise in ML model architecture, hardware/software optimization, and the ability to analyze performance bottlenecks across Qualcomm's hardware/software stack. You will serve as a technical leader, influencing system architecture, working with hardware teams on silicon design, and driving solutions from research through production.

Design and develop machine learning models for computer vision domains including optical flow, depth estimation, visual tracking, SLAM, and 3D reconstruction on Qualcomm Snapdragon platforms. Own end-to-end algorithm implementation from research through production deployment, including training pipeline development, dataset creation, model optimization, and on-device performance tuning.…See more Lead technical direction across projects, influence system-level architecture, and partner with hardware engineers on silicon design. Requires 6+ years of software/hardware/systems engineering experience (or equivalent with Master's/PhD) and demonstrated expertise in on-device ML deployment, neural network optimization, and computer vision algorithm development.

Design, develop, and optimize machine learning systems for production AI platforms, including model development, inference optimization, and scalable ML infrastructure. Build training-to-deployment pipelines, optimize model serving for latency and cost, and integrate LLMs and generative AI models into microservices and APIs.…See more Develop data pipelines for ingestion, preprocessing, and feature engineering while collaborating cross-functionally with product, platform, and hardware teams to deliver end-to-end ML solutions.