AI Systems Hardware Engineer
QualcommJob Title
AI Systems Hardware Engineer
Role Summary
Design and evaluate end-to-end mappings of modern AI workloads onto Qualcomm next-generation SoC and accelerator systems. The role focuses on identifying system and technology bottlenecks and optimizing power, performance, and total cost of ownership (TCO) across SoC, memory, and networking for workloads such as mixture-of-experts (MoE), multi-tenant vector databases, and multimodal AI.
The engineer will use internal and external tools to run workload what-if scenarios, quantify trade-offs, and collaborate with Architecture, Product Management, and Software teams to define implementation strategies for datacenter, physical AI, and device use cases. This position is expected to comply with the company's onsite work policy.
Experience Level
Mid-level — position requires experienced engineering expertise; see Education Requirements for degree-specific years-of-experience guidance.
Responsibilities
Accountabilities include workload characterization, system-level analysis, and cross-functional collaboration to inform architecture and implementation choices.
- Map AI workloads to Qualcomm next-generation accelerator and SoC architectures using internal and external tools.
- Run what-if scenarios to evaluate power, performance, and TCO trade-offs across SoC, memory, and networking.
- Identify system and technology bottlenecks for state-of-the-art and emerging AI workloads (e.g., MoE, vector DBs, multimodal AI).
- Develop and automate analysis workflows and scripts to accelerate workload evaluation and comparisons.
- Collaborate with architecture, product management, and software teams to define implementation strategies and requirements.
- Translate analysis results into actionable recommendations for multiple business units (datacenter, physical AI, compute devices).
- Present findings and trade-offs to technical and non-technical stakeholders; support negotiation of design decisions.
Requirements
Technical skills and attributes required to perform the role.
- Proven experience with ASIC design/verification/validation/integration workflows and system-level evaluation.
- Strong proficiency in scripting (Python or similar) for automating workload mapping and analysis.
- Deep understanding of system KPIs (power, performance, TCO) and how they relate to workload behavior.
- Familiarity with state-of-the-art AI workloads and ability to quickly learn and model new workloads.
- Experience using internal or external performance and simulation tools for workload/system analysis.
- Strong analytical, deductive and inductive problem-solving skills, and advanced data interpretation abilities.
- Effective verbal and written communication skills; ability to influence cross-functional teams.
- Ability to work independently and in teams on problems without fully defined processes.
- Preferred: demonstrated creativity and experience shaping product or process decisions under uncertainty.
Education Requirements
One of the following is required: Bachelor's degree in Science, Engineering, or related field with 6+ years of ASIC-related experience; OR Master's degree in Science, Engineering, or related field with 5+ years of ASIC-related experience; OR PhD in Science, Engineering, or related field with 4+ years of ASIC-related experience. Preferred fields include Electrical Engineering or Computer Science.
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.
