Sr Engineer: LPAI Architecture and Systems Engineer

• Company:

Qualcomm India Private Limited

• Job Area:

Engineering Group, Engineering Group > Systems Engineering

• General Summary:

Job Overview

As part of Qualcomm’s Audio and Low-Power AI (LPAI) Architecture group, you will architect, analyze, and optimize DSP and embedded NPU (eNPU) performance across Snapdragon value-tier platforms. Your focus will be on architectural analysis, optimization, and deployment of low-power AI (LPAI) solutions, enabling efficient on-device intelligence, including eNPU scheduling, memory hierarchy, compression/quantization strategies, and clock/BW voting, to enable efficient on-device AI for audio, sensors, and always-on use cases. You will build system models, conduct performance/power trade studies, and drive architectural recommendations that scale across mobile, XR, compute, IoT, and automotive tiers

Key Responsibilities

· Analyze, design, and optimize LPAI (Hexagon DSP, eNPU, TCM/UBUF/LLC/DDR) for performance, power, and area efficiency in value tier chipsets.

· Conduct architectural analysis and benchmarking of LPAI subsystems, identifying bottlenecks and proposing solutions for improved throughput and efficiency.

· Collaborate with hardware and software teams to define and implement enhancements in DSP/eNPU microarchitecture, memory hierarchy, and dataflow.

· Develop and validate performance models for AI workloads, including signal processing and ML inference, on embedded platforms.

· Prototype and evaluate new architectural features for LPAI, including quantization, compression, and hardware acceleration techniques.

· Support system-level integration, performance testing, and demo prototyping for commercialization of optimized DSP/eNPU solutions.

· Work closely with cross-functional teams to ensure successful deployment and commercialization of value tier chipset features.

· Document architectural analysis, optimization strategies, and performance results for internal and external stakeholders.

Requirements

· Solid background in DSP architecture, embedded NPU design, and low-power AI systems.

· Proven experience in performance analysis, benchmarking, and optimization of embedded processors (DSP, NPU, ARM, RISC-V).

· Strong fundamentals of Power modeling and Power analysis

· Experience working on System level power anlaysis and measurements

· Strong programming skills in Embedded C/C++, Python familiarity with performance modeling tools.

· Experience with embedded platforms, real-time operating systems, and hardware/software co-design.

· Expertise in both fixed-point and floating-point implementation, with a focus on ML/AI workloads.

· Excellent communication, presentation, and teamwork skills; ability to work independently and across global teams.

Educational Qualifications

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

Preferred Qualifications

· Familiarity with Qualcomm DSP/eNPU architectures, SDKs, and tools.

· Experience with LPAI frameworks and design.

· Knowledge of audio or Sensor signal processing frameworks is a plus.

• Minimum Qualifications:

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

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• · Solid background in DSP architecture, embedded NPU design, and low-power AI systems.
• · Proven experience in performance analysis, benchmarking, and optimization of embedded processors (DSP, NPU, ARM, RISC-V).
• · Strong fundamentals of Power modeling and Power analysis
• · Experience working on System level power anlaysis and measurements
• · Strong programming skills in Embedded C/C++, Python familiarity with performance modeling tools.
• · Experience with embedded platforms, real-time operating systems, and hardware/software co-design.
• · Expertise in both fixed-point and floating-point implementation, with a focus on ML/AI workloads.
• · Excellent communication, presentation, and teamwork skills; ability to work independently and across global teams.
• Educational Qualifications
• · Master’s or PhD degree in Engineering, Electronics and Communication, Electrical, Computer Science, or related field.
• · Familiarity with Qualcomm DSP/eNPU architectures, SDKs, and tools.
• · Experience with LPAI frameworks and design.
• · Knowledge of audio or Sensor signal processing frameworks is a plus.