AI Compute Systems Engineer (up to Staff)
QualcommJob Title
AI Compute Systems Engineer (up to Staff)
Role Summary
The AI Compute Systems Engineer will analyze AI compute use cases and model system-level KPIs to influence future AI-first SoC and platform architectures. The role sits within ASICs/ASICS Engineering and collaborates with architecture, systems, and process teams to map AI workload requirements to chip integration and technology roadmaps.
Experience Level
Senior (up to Staff). Experience guidance in the posting: roughly 3–8+ years in AI compute, system architecture, or related roles; other degree-based minimums specify 2–4+ years depending on degree.
Responsibilities
Primary responsibilities focus on system-level analysis, modeling, and cross-functional integration to shape chip and integration strategies for AI workloads.
- Analyze AI workloads and quantify dependencies on power, latency, bandwidth, and other system KPIs.
- Develop modeling frameworks (e.g., Python) to evaluate how 3D/heterogeneous architectures and chiplet strategies affect compute efficiency.
- Collaborate with architects, systems engineers, and process teams to translate AI requirements into chip integration and technology roadmaps.
- Study interactions among CPU, GPU, NPU, and other IP blocks within end-to-end AI pipelines.
- Explore trends in AI compute architectures, accelerators, and chip-integration strategies; provide guidance for exploratory R&D directions.
- Define, model, verify, validate, and document IP and SoC-level implementations as needed for product development.
Requirements
Must-have technical skills and experience expected for the role.
- Strong understanding of AI use cases and system-level KPI dependencies (power, latency, bandwidth).
- Proficient in programming and modeling (Python or similar) to build analysis frameworks.
- 3–8+ years of relevant experience in AI compute, system architecture, or closely related areas.
- Experience or demonstrated ability to work across architecture, systems, and process teams to map requirements to integration strategies.
- Ability to study and reason about end-to-end pipelines and interactions among heterogeneous IP blocks.
- Preferred: experience with heterogeneous compute architectures and working in exploratory R&D environments.
Education Requirements
Degrees accepted: Bachelor's, Master's, or PhD in Science, Engineering, EE, CE, CS, or related technical fields. The posting specifies degree-plus-experience combinations: Bachelor's + 4+ years, Master’s + 3+ years, or PhD + 2+ years; other language allows related work experience in lieu of degree.
About the Company
Company: Qualcomm
Headquarters: San Diego, California, United States
Qualcomm is a global leader in semiconductor and telecommunications equipment, specializing in mobile technologies and innovations. Known for its Adreno GPUs, the company provides solutions enabling advancements in mobile gaming, AI, VR/AR, and autonomous driving. Qualcomm's cutting-edge technology and commitment to high-performance, power-efficient designs drive the evolution of mobile graphics and connectivity worldwide.
