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Systems Engineer, Data Center AI Systems Engineering

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Qualcomm
Full Time position
Listed on 2026-09-12
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 111300 - 166900 USD Yearly USD 111300.00 166900.00 YEAR
Job Description & How to Apply Below
## Systems Engineer, Data Center AISan Diego, California, United States of America Apply Now Find out how well you match with this jobJob ID3094096##
** Company:
** Qualcomm Technologies, Inc.##
** Job Area:
** Engineering Group, Engineering Group  Systems Engineering
** General

Summary:

** 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 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 Systems 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.
*
* Minimum Qualifications:

*
* • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
OR  Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
OR  PhD in Engineering, Information Systems, Computer Science, or related field.
*
* Principal Duties and Responsibilities:

*** Develop AI/ML solutions that bring together Qualcomm AI hardware products, technologies, software, and ecosystem and provide best-in-class AI inference performance, power efficiency and scalability
* Assist in the design, development, implementation and deployment of Gen AI and LLM applications
* Contribute towards implementing fine tuning and distillation techniques
* Apply Systems knowledge and experience to research, design, develop, simulate, and/or validate systems-level software, AI hardware, architecture, deep learning algorithms, and AI solutions while ensuring system-level requirements and standards are met
* Perform AI model benchmarking and functional analysis to drive requirements and specifications
* Propose deployment strategies with AI model/workload optimization and deployment
* Build AI solutions and develop and analyze system level design including requirements, interface definition, functional/performance definition, and implementation of a new system or modification of an existing system
* Collaborate with own team and other teams to complete project work, including implementing and testing features and verifying the accuracy of AI systems
* Keep abreast with the latest advancements in the AI/ML space (models, HW/SW) and drive innovative solutions.
* Develops new and innovative ideas for a product or feature area
* Drives triage of problems at the system level to determine root cause and presents results of testing and debugging to team members.
*
* Required Skills:

*** Strong proficiency in Python, and ML frameworks (PyTorch, Tensor Flow).
* Deep understanding of ML development, deployment and applications.
* Deep understanding of system performance profiling and parallel computing.
*
* Preferred Qualifications:

*** Master's or PhD Degree in Engineering, Information Systems, Computer Science, Physics or related field
* Good understanding of GenAI architectures from transformers, diffusion, hybrid - LLMs, LVMs, embeddings
* Working experience with fine-tuning GenAI models and Reinforcement Learning
* Background in compiler optimizations for ML workloads is a plus
* Experience with architectural Patterns for Large-Scale AI Systems:
Knowledge of microservices, and distributed systems
* Optimize…
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