Embedded ML Staff Engineer -- Snapdragon Mobile

Company: Qualcomm Technologies, Inc. Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Seeking an experienced Embedded ML Staff Engineer focused on Snapdragon Mobile products. As a senior individual contributor on the team working on Mobile Handset software architecture and system design and development, you will analyze requirements and design/implement solutions for new use-cases and features. You will drive technical initiatives to evolve Snapdragon Mobile AI software, helping deliver performance and power enhancements into the SW/HW stacks and tools of state-of-the-art machine learning solutions. You will work closely with architects, development leads, software and hardware engineers, project engineers, and product managers. Ideal candidate has strong experience with Mobile SW design and deployment, system SW performance optimization, benchmarking, and performance breakdown analysis with CPU, GPU, NPU, and knowledge of state of the art in AI for one or more of the domains such as Computer Vision, Audio, Generative AI. Hands-on experience with agentic AI systems, LLMs/SLMs, and embedded ML at the system level on resource-constrained devices, including heterogeneous compute placement across CPU/GPU/NPU and context/perception pipelines that feed those experiences, is a strong plus. Experience with Mobile platforms is highly desirable. Strong written and verbal communication skills are important. Strong collaboration and mentorship skills are a plus.   Minimum Qualifications: • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Design and implement architecture for complex AI features and experiences within your subsystem for Snapdragon Mobile products; propose architecture improvements.   Research and collaborate cross-functionally to help define requirements; build hands-on prototypes.   Design and implement on-device agentic experience components, including context and memory management, perception (e.g., screen/scene understanding, sensor fusion), and heterogeneous compute placement for LLM/SLM workloads across CPU, GPU, and NPU under tight power, thermal, and memory budgets.   Implement closed-loop, telemetry-driven resource scheduling components for heterogeneous compute (CPU/GPU/NPU), re-evaluating workload placement against live power, thermal, and SLA signals.   Implement memory and model-state lifecycle management for on-device LLM/SLM serving -- including KV-cache and context-state caching, eviction, paging, and reuse/sharing across sessions under tight device memory budgets.   Evaluate and help architect around memory bandwidth and data-movement constraints (e.g., high-bandwidth memory, on-chip interconnects) to maximize achievable AI throughput and efficiency on constrained silicon.   Serve as a technical resource in design reviews; recommend improvements aligned to business and customer needs.   Collaborate with external partners on subsystem implementation plans and milestones.   Stay current on AI and Mobile industry trends, competitors' products, and advances in various engineering fields; share expertise within the team.   Contribute technical input and trend analysis to roadmap discussions led by architecture and product leadership.

Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch). Experience with large language models/foundational models and small