AI Compute Systems Engineer, up to Staff

Location: Hsinchu City, Hsinchu City, Taiwan, Seoul, Korea, Republic of, Seoul, Seoul, Korea, Republic of

Department: ASICS Engineering

Work Location: onsite

Company:

Qualcomm Semiconductor Limited

Job Area:

Engineering Group, Engineering Group > ASICS Engineering

General Summary:

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.

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
- 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.
 

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