Job description

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 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. Preferred Qualifications: • 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 Principal Duties and Responsibilities: • 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 Minimum Qualifications: • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. 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). To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification. Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. Pay range and Other Compensation & Benefits : $169,800.00 - $254,600.00 The 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 .

Requirements

Must-haves

Qualcomm Technologies, Inc.
Engineering Group, Engineering Group > Systems Engineering
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.
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

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningpythonmlrestdockerkubernetesllm

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