Sr Engineer: LPAI Architecture and ...

Senior Engineer: LPAI Architecture and Systems Engineering at Qualcomm India Private Limited

Qualcomm India Private Limited is seeking a talented Senior Engineer to join their Engineering Group, specifically within the Systems Engineering team. This role focuses on the architecture, analysis, and optimization of Digital Signal Processors (DSP) and embedded Neural Processing Units (eNPU) for Snapdragon value-tier platforms.

Job Overview

As a key member of Qualcomm's Audio and Low-Power AI (LPAI) Architecture group, you will play a crucial role in architecting, analyzing, and optimizing DSP and embedded NPU performance across various Snapdragon value-tier platforms. Your primary responsibilities will involve the architectural analysis, optimization, and deployment of low-power AI (LPAI) solutions. This enables efficient on-device intelligence, encompassing aspects like eNPU scheduling, memory hierarchy management, compression and quantization strategies, and clock/bandwidth voting. The goal is to facilitate efficient on-device AI for audio, sensor, and always-on use cases. You will be responsible for building system models, conducting performance and power trade studies, and driving architectural recommendations that can scale across mobile, XR, compute, IoT, and automotive tiers.

Key Responsibilities

• Analyze, design, and optimize LPAI components (Hexagon DSP, eNPU, TCM/UBUF/LLC/DDR) for superior performance, power efficiency, and area optimization in value-tier chipsets.
• Conduct thorough architectural analysis and benchmarking of LPAI subsystems to identify performance bottlenecks and propose effective solutions for improved throughput and efficiency.
• Collaborate closely with hardware and software engineering teams to define and implement enhancements in DSP/eNPU microarchitecture, memory hierarchy, and dataflow.
• Develop and validate robust performance models for AI workloads, including signal processing and machine learning inference, on embedded platforms.
• Prototype and evaluate novel architectural features for LPAI, such as advanced quantization, compression techniques, and hardware acceleration.
• Provide support for system-level integration, performance testing, and demo prototyping to facilitate the commercialization of optimized DSP/eNPU solutions.
• Work hand-in-hand with cross-functional teams to ensure the successful deployment and commercialization of value-tier chipset features.
• Document comprehensive architectural analyses, optimization strategies, and performance results for dissemination to internal and external stakeholders.

Requirements

• A strong foundation in DSP architecture, embedded NPU design, and low-power AI systems.
• Demonstrated experience in performance analysis, benchmarking, and optimization of embedded processors (DSP, NPU, ARM, RISC-V).
• Solid understanding of power modeling and power analysis principles.
• Experience in system-level power analysis and measurements.
• Proficiency in Embedded C/C++ programming, with familiarity in Python and performance modeling tools.
• Hands-on experience with embedded platforms, real-time operating systems, and hardware/software co-design methodologies.
• Expertise in both fixed-point and floating-point implementations, with a particular focus on ML/AI workloads.
• Exceptional communication, presentation, and teamwork skills, with the ability to work both independently and collaboratively across global teams.

Educational Qualifications

• Master's or PhD degree in Engineering, Electronics and Communication, Electrical, Computer Science, or a related field.

Preferred Qualifications

• Familiarity with Qualcomm DSP/eNPU architectures, Software Development Kits (SDKs), and associated tools.
• Prior experience with LPAI frameworks and design methodologies.
• Knowledge of audio or sensor signal processing frameworks is considered a significant advantage.

Minimum Qualifications

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