Senior Systems Engineer, Data Center AI
Qualcomm · San Diego, United States · 8d ago
Company:
Qualcomm Technologies, Inc.Job Area:
Engineering Group, Engineering Group > Systems EngineeringGeneral 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, TensorFlow).
- 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 inference performance across heterogenous nodes CPUs, GPUs, and specialized accelerators
- Experience in implementing caching, batching, and parallelization strategies for high-throughput systems.
- Familiarity with hardware acceleration
- Proficiency with version control systems (Git) and code review tools (Gerrit, GitHub, GitLab) and collaborative development workflows
- Well versed with open-source development practices
- Understanding of MLOps for AI application development and deployments is a plus
- Experience with automation tools like GitOps, containerization technologies (Docker, Kubernetes), ML lifecycle management tools is a plus
- Experience with rack-level orchestration tools and data center automation is a plus
- Experience working in a large matrixed organization
Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
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Pay range and Other Compensation & Benefits:
$117,800.00 - $176,600.00The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.