About the job
The Qualcomm Cloud AI team is developing software solutions for Inference Acceleration. We are seeking an ambitious, bright and innovative engineer who has delivered commercial software and experience spanning design, compiler technology, performance modeling, and bottleneck analysis. Job activities span the whole product life cycle from early R&D to commercial deployment. The environment is fast-paced and requires cross-functional interaction on a daily basis so good communication, planning and execution skills are a must. We are looking to staff engineers at multiple levels in systems & software, integration and test. Details of one of the roles we are looking to staff are listed below. Backfill position
Responsibilities
Proven ability of planning, managing and deliver large commercial software projects; Experience in serving frameworks, like vLLM; Strong development skills in PyTorch; Strong understanding of LLMs, Multi-modal and reasoning models; Experience in executing, analyzing, and optimizing neural networks; Experience in writing high performance software for multicore systems; Experience with C++, Python; Strong skills in analyzing performance of software/hardware solutions on multi-core architectures; understanding of multi-core architecture fundamentals (core, cache, memory, bus, PCIe, etc); Understanding of multi-core processor architecture and SoC architectures (NoCs, caches, memories, etc.); Experience with Performance modeling of SoC architectures; Excellent communication skills (written and verbal) and team player; Experience with machine learning accelerators and related software is highly desired; Background and understanding of neural network operators and mathematical operations: linear algebra, math libraries, desirable
Qualifications
Minimum
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.
Preferred
No preferred qualifications listed.