Datacenter AI Systems and Solutions Engineer, Sr Staff

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all.

As a Qualcomm Datacenter AI Systems and Solutions Engineer, you will research, develop, optimize, and validate software, hardware, architecture, algorithms, and machine learning solutions that enable the deployment of cutting-edge AI datacenter technology.

Qualcomm Solution Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. This is a great opportunity to innovate and develop leading-edge products and solutions around best-in-class Qualcomm AI inference accelerators for data center, and hybrid AI applications.

* Master's or PhD in Engineering, Computer Science, Information Systems, Physics, or a related discipline

* Strong proficiency in Python and experience with ML frameworks, APIs, REST services, and microservice-based architecture

* Hands-on experience designing, deploying, and operating AI/ML systems in production

* Solid understanding of Generative AI architectures, including transformers, diffusion models, and hybrid systems (LLMs, LVMs, embeddings)

* Experience with large-scale AI systems architecture, including microservices, distributed systems, event-driven designs, and fault-tolerant/resilient architectures

* Practical experience with AI inference serving, performance optimization, and scalability across heterogeneous hardware

* Experience with MLOps practices for AI application development, deployment, monitoring, and lifecycle management

* Familiarity with automation and DevOps tooling, including GitOps workflows, containerization (Docker), orchestration platforms (Kubernetes), and ML lifecycle tools

* Strong problem-solving skills with a customer and solution-focused mindset

* Experience with cluster schedulers and resource managers (e.g., Slurm, PBS) and workload orchestration is a plus

* Experience with observability, monitoring, and debugging tools for ML pipelines and inference services

* Proven ability to operate effectively in a large, matrixed organization, influencing across teams

* Experience with fine-tuning and optimization of GenAI models, including reinforcement learning techniques, is a plus

* Well versed in open-source development practices, collaboration, and code quality standards

* Exposure to rack-level orchestration, fleet management, and data center automation is a plus

* Lead the development of end-to-end AI/ML solutions that integrate Qualcomm AI hardware, system software, and ecosystem components to deliver best-in-class AI inference performance, power efficiency, and scalability

* Drive the design, development, deployment, and optimization of Generative AI and LLM-based applications, with a focus on production readiness and inference efficiency

* Contribute to and guide the implementation of model fine-tuning, distillation, and optimization strategies tailored for deployment on target hardware

* Apply deep systems-level expertise to research, design, develop, simulate, validate, and optimize AI systems spanning hardware, system software, AI frameworks, and models, while ensuring system-level requirements are met

* Perform AI model benchmarking, workload characterization, and performance analysis to influence system requirements, hardware/software co-design, and product direction

* Serve as a technical lead for customer engagements, supporting AI model onboarding, inference optimization, deployment, and performance tuning

* Own and drive system-level architecture and design, including requirements definition, interface specifications, performance targets, and implementation of new systems or enhancements to existing platforms

* Collaborate across cross-functional teams (hardware, software, tools, frameworks, and product) to deliver features, validate AI system correctness, and ensure high-quality execution

* Stay current with advancements in AI/ML models, inference techniques, and hardware/software innovations, and proactively translate them into impactful solutions

* Propose and drive new, innovative ideas that meaningfully improve products, platforms, or developer experience

* Lead system-level debugging and triage, identify root causes across the stack, and clearly communicate findings, trade-offs, and recommendations to team members and stakeholders

- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.

Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience.

PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.