Staff/Sr Staff System AI Performance Engineer

Qualcomm · Bengaluru · 6+ yrs experience · Posted 2026-04-10

Tech stack: Python

Apply on the company site · Get a referral for this role

Qualcomm salary & ratings · Qualcomm interview process · More live openings

About the role

Qualcomm India Private Limited
Engineering Group, Engineering Group > Systems Engineering
Responsibilities: - We are seeking a highly skilled engineer to enable highly optimized mapping of AI workloads to Qualcomm’s next generation system-technology solutions for the slowing Moore’s law era.
- The focus is on identifying the system and technology bottlenecks for the state-of-the-art and emerging AI workloads e.g. the mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI etc..
- The E2E system KPIs for mapping these emerging AI workloads include the power, performance and TCO of the entire system encompassing the SoC, memory and networking.
- The primary role of the candidate is to map the workloads using both internal and external tools to Qualcomm’s next-gen AI accelerator systems and carry out what-if scenarios of optimizing different underlying components e.g. SoC, memory, networking and other technology features for the best power-performance-TCO trade-off.
- The candidate also needs to ensure which AI workloads are relevant for the different business units (BUs) from datacenters to physical AI to computing devices.
- To drive these technologies the person will collaborate with high-level representatives across functional teams (e.g. Architecture, product management, SW teams) to enable an implementation strategy that meets system requirements.
Qualifications: - Bachelor's degree in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.
- Master's degree in Science, Engineering, or related field and 5+ years of ASIC design, verification, validation, integration, or related work experience.
- PhD in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience.
- Thorough understanding of E2E system KPI dependency e.g. power, performance and TCO of emerging AI workloads mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI.
- Ability to quickly map newer workloads onto Qualcomm systems using internal and external tools so high proficiency in scripting (python or similar) is required.
- Great knowledge of state-of-art workloads across multiple BUs.
- Master's or Ph.D. in Electrical Engineering, Computer Science, or a related field
- Exceptional creativity to innovate new ideas and develop innovative products/ processes without established objectives or known parameters.
- Verbal and written communication skills to convey highly complex and/or detailed information.
- Will require strong negotiation and influence with large groups or high-level constituents
- Ability to work independently and as part of a team
- Most tasks do not have defined steps; simultaneous use of multiple mental abilities is generally required to determine the best approach
- Deductive and inductive problem solving is required; multiple approaches may be taken/necessary to solve the problem; often information is missing or conflicting; advanced data analysis and interpretation skills are required.
- Keywords: LLM, Computer Architecture, Performance Analysis
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

Qualifications

- Bachelor's degree in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.
- Master's degree in Science, Engineering, or related field and 5+ years of ASIC design, verification, validation, integration, or related work experience.
- PhD in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience.
- Thorough understanding of E2E system KPI dependency e.g. power, performance and TCO of emerging AI workloads mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI.
- Ability to quickly map newer workloads onto Qualcomm systems using internal and external tools so high proficiency in scripting (python or similar) is required.
- Great knowledge of state-of-art workloads across multiple BUs.
- Master's or Ph.D. in Electrical Engineering, Computer Science, or a related field
- Exceptional creativity to innovate new ideas and develop innovative products/ processes without established objectives or known parameters.
- Verbal and written communication skills to convey highly complex and/or detailed information.
- Will require strong negotiation and influence with large groups or high-level constituents
- Ability to work independently and as part of a team
- Most tasks do not have defined steps; simultaneous use of multiple mental abilities is generally required to determine the best approach
- Deductive and inductive problem solving is required; multiple approaches may be taken/necessary to solve the problem; often information is missing or conflicting; advanced data analysis and interpretation skills are required.
- Keywords: LLM, Computer Architecture, Performance Analysis
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.
- Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience.
- PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.

Responsibilities

- We are seeking a highly skilled engineer to enable highly optimized mapping of AI workloads to Qualcomm’s next generation system-technology solutions for the slowing Moore’s law era.
- The focus is on identifying the system and technology bottlenecks for the state-of-the-art and emerging AI workloads e.g. the mixture-of-experts (MoE), multi-tenant vector databases, multimodal physical AI etc..
- The E2E system KPIs for mapping these emerging AI workloads include the power, performance and TCO of the entire system encompassing the SoC, memory and networking.
- The primary role of the candidate is to map the workloads using both internal and external tools to Qualcomm’s next-gen AI accelerator systems and carry out what-if scenarios of optimizing different underlying components e.g. SoC, memory, networking and other technology features for the best power-performance-TCO trade-off.
- The candidate also needs to ensure which AI workloads are relevant for the different business units (BUs) from datacenters to physical AI to computing devices.
- To drive these technologies the person will collaborate with high-level representatives across functional teams (e.g. Architecture, product management, SW teams) to enable an implementation strategy that meets system requirements.

More openings at Qualcomm