AI Compute Systems Engineer
Qualcomm
Job Overview
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Job Description
General Summary
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives communication and data processing transformation to help create a smarter, connected future for all. As a Qualcomm ASIC Engineer, you will define, model, design (digital and/or analog), optimize, verify, validate, implement, and document IP (block/SoC) development for a variety of high performance, high quality, low power world class products. Qualcomm Engineers collaborate with cross-functional groups to determine product execution path.
Role Focus
This role centers on analyzing AI compute use cases and modeling system‑level KPIs to influence Qualcomm’s future AI‑first SoC and platform architectures. The engineer will bridge AI workload behavior with process technology and chiplet/3D integration strategies.
Key Responsibilities
- Analyze AI workloads and their dependencies on system KPIs (power, latency, bandwidth).
- Build modeling frameworks (e.g., Python) to evaluate how 3D/heterogeneous architectures impact compute efficiency.
- Collaborate with architecture, systems, and process teams to map AI requirements to chip integration and technology roadmaps.
- Study the interaction 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.
Minimum Qualifications
- Bachelor's degree in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience. OR
- Master's degree in Science, Engineering, or related field and 3+ years of ASIC design, verification, validation, integration, or related work experience. OR
- PhD in Science, Engineering, or related field and 2+ years of ASIC design, verification, validation, integration, or related work experience.
- Strong understanding of AI use cases and system-level KPI dependencies.
- Basic programming and modeling skills (Python or similar).
- Master’s or PhD in EE/CE/CS or related field.
- 3–8+ years of AI compute, system architecture, or related experience.
Preferred Qualifications
- Knowledge of end-to-end AI pipelines.
- Experience in heterogeneous compute architectures.
- Ability to operate effectively in exploratory R&D environments.
Key skills/competency
- AI Workload Analysis
- System KPI Modeling
- 3D/Heterogeneous Architectures
- Chiplet/3D Integration
- ASIC Design
- SoC Architecture
- Python Programming
- End-to-End AI Pipelines
- AI Accelerators
- Low Power Design
How to Get Hired at Qualcomm
- Research Qualcomm's AI vision: Study their commitment to AI-first architectures, recent innovations, and strategic direction in semiconductor technology.
- Tailor your resume for AI systems: Customize your application to highlight experience in AI workload analysis, system KPI modeling, and heterogeneous compute architectures.
- Showcase modeling and Python skills: Emphasize projects or experiences demonstrating proficiency in building modeling frameworks with Python or similar languages for complex system evaluations.
- Prepare for architectural discussions: Be ready to discuss your understanding of ASIC design, SoC development, 3D/chiplet integration, and end-to-end AI pipelines during interviews.
- Demonstrate collaborative experience: Provide examples of successful cross-functional collaboration with architecture, systems, and process teams in R&D environments.
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