Senior Engineer- Power Architecture and Systems Engineer

Qualcomm; Hyderabad; On-site; INR 800,000 - 1,200,000; Full time

Job summary

Qualcomm is seeking an engineer for audio and low-power AI systems in Hyderabad. The role involves optimizing power efficiency for DSP/eNPU subsystems, requiring expertise in power modeling and embedded platforms.

The ideal candidate will possess strong programming skills in Python, alongside a degree in Electrical Engineering or related fields. This position offers opportunities to collaborate with cross-functional teams on cutting-edge AI technology.

Qualifications

• 2+ years of experience in Systems Engineering for Bachelor's degree holders.
• 1+ year of experience in Systems Engineering for Master's degree holders.
• Knowledge of fixed-point implementation and low-power optimization techniques.

Responsibilities

• Analyze and optimize power consumption of LPAI subsystems.
• Develop system-level power analysis to evaluate audio use cases.
• Perform detailed data-path and memory-access analysis for efficiency.

Skills

Power modeling

Power analysis

Python programming

Memory systems understanding

Embedded platforms experience

Education

Bachelor's/Master's/PhD in Electrical Engineering

Bachelor's in Engineering or related

Tools

Power measurement tools

Performance/power profiling tools

Job description

Company

Qualcomm India Private Limited

Job Area

Engineering Group, Engineering Group > Systems Engineering

General Summary

As part of Qualcomm’s Audio and Low-Power AI (LPAI) Systems group, this role focuses on power and data-path analysis, optimization, and architecture of embedded AI subsystems, with emphasis on XR and always‑on use cases. The engineer will drive power‑efficient system design and analysis across DSP/eNPU subsystems by analyzing power‑performance trade‑offs, and enabling optimizations across memory access, data movement, and workloads for on‑device AI.

Key Responsibilities

• Analyze and optimize power consumption of LPAI subsystems (DSP, eNPU, memory hierarchy) with focus on XR and always‑on AI workloads.
• Develop system‑level power analysis to evaluate different audio use cases across DSP abd eNPU.
• Perform detailed data-path and memory‑access analysis (TCM, LLC, DDR) to identify bottlenecks impacting power efficiency.
• Drive power optimization techniques including clock/BW voting, workload partitioning, scheduling, and data reuse strategies.
• Collaborate with HW, SW, and PdM teams to review eNPU power architecture and low‑power feature roadmap.
• Execute lab‑based power measurements, correlate silicon data with modelling, and propose optimization strategies.
• Support system integration, benchmarking, and commercialization of power‑optimized LPAI solutions across Mobile, XR, Compute, and IoT platforms.
• Document power analysis methodologies, findings, and architectural recommendations for internal stakeholders.

Requirements

• Strong fundamentals in power modeling, power analysis, and system‑level power optimization.
• Experience with embedded processor architectures such as DSPs and NPUs, with understanding of eNPU power behavior.
• Hands‑on experience with power measurement setups such as Kratos, tools, and data analysis techniques.
• Strong programming skills in Python for analysis, modeling, and automation.
• Solid understanding of memory systems, data movement, bandwidth analysis, and Cache memory strategies.
• Experience working with embedded platforms, RTOS, and performance/power profiling tools.
• Knowledge of fixed‑point implementation and low‑power optimization techniques.
• Ability to work across cross‑functional and geographically distributed teams.

Preferred Qualifications

• Experience with Qualcomm DSP and LPAI architectures, SDKs, or internal power tools.
• Background in audio, or always‑on AI use cases.
• Exposure to ML inference workloads and their power‑performance characteristics.

Educational Qualifications

Bachelor’s/Master’s/PhD degree in Electrical Engineering, Electronics and Communication, Computer Science, or related field.

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
• Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
• PhD in Engineering, Information Systems, Computer Science, or related field.

Equal Opportunity Employer

Qualcomm is an equal opportunity employer.