LPAI Architecture and Systems Engineer

Company

Job Area

General Summary

• 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 programming skills in Embedded C/C++, Python, and Matlab; 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.
  

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience.