Senior Systems Engineer, Data Center AI
About The Position
Qualcomm Technologies, Inc. is seeking a Senior Systems Engineer to research, develop, optimize, and validate software, hardware, architecture, algorithms, and machine-learning solutions for deployment of advanced AI data-center technology. The role focuses on bringing together Qualcomm AI hardware, software, technologies, and ecosystem capabilities to deliver strong AI-inference performance, power efficiency, and scalability for data-center and hybrid AI applications. The engineer will help design, develop, implement, and deploy generative AI and large language model applications; contribute to fine-tuning and distillation approaches; and conduct model benchmarking and functional analysis. The position involves systems-level research and design, workload and model optimization, deployment strategy development, and analysis of system requirements, interfaces, functions, and performance. The engineer will collaborate across teams to implement and test features, validate AI systems, investigate system-level problems, and keep current with AI/ML developments to identify innovative product and feature ideas.
Requirements
- Bachelor’s degree in Engineering, Information Systems, Computer Science, or a related field and at least 2 years of Systems Engineering or related work experience; or a master’s degree in one of these fields and at least 1 year of related experience; or a Ph.D. in one of these fields.
- Strong proficiency in Python and ML frameworks such as PyTorch and TensorFlow.
- Deep understanding of ML development, deployment, and applications.
- Deep understanding of system performance profiling and parallel computing.
Nice To Haves
- Master’s or Ph.D. degree in Engineering, Information Systems, Computer Science, Physics, or a related field.
- Good understanding of generative AI architectures, including transformers, diffusion, hybrid models, LLMs, LVMs, and embeddings.
- Working experience fine-tuning generative AI models and with reinforcement learning.
- Background in compiler optimizations for ML workloads.
- Experience with architectural patterns for large-scale AI systems, including microservices and distributed systems.
- Experience optimizing inference performance across heterogeneous CPU, GPU, and specialized-accelerator nodes.
- Experience implementing caching, batching, and parallelization strategies for high-throughput systems.
- Familiarity with hardware acceleration.
- Proficiency with version-control systems such as Git and code-review tools such as Gerrit, GitHub, or GitLab, along with collaborative development workflows.
- Familiarity with open-source development practices.
- Understanding of MLOps for AI application development and deployment.
- Experience with automation tools such as GitOps, containerization technologies such as Docker and Kubernetes, and ML lifecycle management tools.
- Experience with rack-level orchestration tools and data-center automation.
- Experience working in a large matrixed organization.
Responsibilities
- Develop AI/ML solutions combining Qualcomm AI hardware products, technologies, software, and ecosystem capabilities to improve inference performance, power efficiency, and scalability.
- Assist in the design, development, implementation, and deployment of generative AI and LLM applications.
- Contribute to implementation of model fine-tuning and distillation techniques.
- Research, design, develop, simulate, and/or validate systems-level software, AI hardware, architecture, deep-learning algorithms, and AI solutions while meeting system-level requirements and standards.
- Perform AI model benchmarking and functional analysis to drive requirements and specifications.
- Propose deployment strategies involving AI model and workload optimization.
- Build AI solutions and develop and analyze system-level designs, including requirements, interface definitions, functional and performance definitions, and implementations of new or modified systems.
- Collaborate with team members and other teams to complete project work, implement and test features, and verify AI system accuracy.
- Monitor advancements in AI/ML models and hardware/software and drive innovative solutions.
- Develop new and innovative ideas for a product or feature area.
- Triage system-level problems to determine root causes and present testing and debugging results to team members.
Benefits
- Competitive annual discretionary bonus program.
- Opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for the annual bonus).
- Competitive benefits package designed to support employees at work, at home, and at play.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
