Engineer, Staff
Qualcomm · Posted Sep 24
Semiconductor, 5G wireless technology, mobile platform, and AI computing solutions
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About the role
The Datacenter AI Systems and Solutions team at Qualcomm works on AI inference on Qualcomm's datacenter AI platform, spanning hardware accelerators, compiler, runtime, serving frameworks and model optimization. As a Staff Engineer, you own the full arc of AI inference programs from architectural decisions through production deployment and serve as the technical lead on customer engagements. The role requires expertise across the AI stack combined with cross-functional leadership across compiler, runtime, serving and customer engineering organizations.
What you will do
- Lead the architecture and end-to-end design of AI inference solutions on Qualcomm AI hardware, defining system requirements, interface specifications and performance targets for complex deployments
- Own customer AI engagements as technical lead: translate customer requirements into deployment-ready serving architectures, drive model optimization and validate production readiness
- Drive development and deployment of GenAI and LLM applications, including architecture decisions for fine-tuning, quantization, speculative decoding and disaggregated serving
- Define and execute benchmarking programs across the hardware and software stack; perform root-cause analysis on complex system-level issues and communicate findings to engineering and customer stakeholders
- Mentor and coach engineers on technical approaches, debugging methodology and best practices; provide leadership on project execution and set clear expectations across contributors
- Identify and prototype solutions to unmet technical challenges; challenge ingrained practices by introducing approaches drawn from current research and validated against production hardware
- Collaborate across compiler, runtime, serving, model engineering and customer engineering teams to resolve cross-functional blockers and deliver system-level objectives
- Define reusable platform capabilities, tooling and documentation that scale team capacity beyond individual engagements
- Contribute to strategic decisions on model portfolio prioritization, inference stack investment and customer deployment architecture
- Track advancements in AI and ML research and translate techniques relevant to Qualcomm's hardware capabilities into actionable product and solution improvements
Skills used in this role
What the employer is looking for
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of systems engineering or related work experience
- OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of systems engineering or related work experience
- OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of related experience
- Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow)
- Deep understanding of ML model development, deployment and production inference
- Deep understanding of system performance profiling and parallel computing
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.
- OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience.
- OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
- 2+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
Preferred qualifications
- Master's or PhD in Engineering, Information Systems, Computer Science, Physics or related field
- Advanced understanding of GenAI architectures including transformers, diffusion models, LLMs, large vision-language models and embedding models
- Hands-on experience with inference optimization techniques: speculative decoding, KV cache management, continuous batching and tensor/pipeline parallelism
- Experience fine-tuning and distilling GenAI models at scale; familiarity with RLHF and RLAIF methods is a plus
- Background in compiler optimizations for ML workloads targeting heterogeneous hardware
- Experience designing and operating large-scale distributed AI systems with knowledge of microservice and event-driven architectures
- Proficiency with MLOps practices and ML lifecycle tooling; experience with containerization and automation (Docker, Kubernetes, GitOps) is expected
- Experience with observability and performance analysis for ML pipelines: metrics collection, distributed tracing and capacity modeling
- Track record of leading complex technical programs across large, matrixed organizations
- Experience with open-source development workflows and version control systems (Git, GitHub, GitLab, Gerrit)
- Experience with rack-level orchestration and datacenter automation is a plus
Benefits and support
- Compensation and benefits are detailed in the job posting
About Qualcomm
Qualcomm is a global leader in the development and commercialization of foundational technologies for the wireless industry, including mobile processors, 5G, and on-device artificial intelligence. The company designs and markets digital communications products, semiconductor solutions, and system software used globally across smartphones, automotive solutions, IoT devices, and computing systems. Through extensive R&D and intellectual property licensing, Qualcomm powers a highly interconnected and smarter world.
- Industry
- Semiconductors
- Company size
- 50000+ employees
- Founded
- 1985
- Location
- San Diego, California, USA
- Funding stage
- Public Company
Funding
Public Company · $53M raised
- 2018-11-01Grant
Leadership
President and Chief Executive Officer
Chief Financial Officer and Chief Operating Officer
James H. Thompson
Chief Technology Officer
Chief Marketing Officer
Ann Chaplin
General Counsel and Corporate Secretary
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