AI Systems Hardware Engineer

What you'll do

• Map emerging AI workloads to next-generation system-technology solutions using internal and external tools.
• Identify system and technology bottlenecks for state-of-the-art workloads like MoE and multi-tenant vector databases.
• Conduct "what-if" scenarios to optimize power, performance, and TCO across SoC, memory, and networking components.
• Determine which AI workloads are relevant for different business units ranging from datacenters to physical AI.
• Develop implementation strategies that meet system requirements by coordinating with architecture, product management, and software teams.
• Perform advanced data analysis to solve complex problems where information may be missing or conflicting.
• Utilize scripting skills in Python or similar languages to map new workloads onto Qualcomm systems.

What we're looking for

• Bachelor's degree in Science, Engineering, or a related field with 6+ years of ASIC design, verification, validation, or integration experience.
• Master's degree in Science, Engineering, or a related field with 5+ years of ASIC design, verification, validation, or integration experience.
• PhD in Science, Engineering, or a related field with 4+ years of ASIC design, verification, validation, or integration experience.
• High proficiency in scripting using Python or similar languages to map workloads onto systems.
• Thorough understanding of E2E system KPI dependencies including power, performance, and TCO for emerging AI workloads.
• Strong verbal and written communication skills to convey complex information and influence high-level constituents.
• Advanced data analysis, interpretation, and problem-solving skills to address tasks with missing or conflicting information.
• Ability to work independently and as part of a team in an environment without established objectives.