Principal Engineer/Senior Staff Engineer- CPU Software & Hardware

QUALCOMM, Inc.; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

QUALCOMM, Inc. in Bengaluru seeks a CPU Software Hardware Co-Design Engineer (ML Systems) to architect and optimize embedded and cloud edge software, spanning ML models to low-level kernels.

The role emphasizes workload characterization, simulation with QEMU, bottleneck analysis, and performance-driven architectural enhancements for next-gen QMX CPUs, including GEMM, convolution, and attention kernels.

Qualifications

• Strong background in Computer Architecture / Systems Programming.
• Solid knowledge of Machine Learning fundamentals.
• Experience with performance profiling, benchmarking, and optimization.

Responsibilities

• ML Workload Identification & Characterization: identify critical ML workloads for CPU-centric execution.
• Simulation Trace Generation: produce traces using QEMU or equivalents and develop tooling to capture performance counters.
• Bottleneck Analysis & Optimization: identify CPU pipelines, memory hierarchy bottlenecks; optimize with kernel tuning and data/layout changes.
• SoftwareHardware Co-Design: collaborate to propose architectural enhancements and feed data-driven insights to CPU design teams.
• ML Kernel Library Development (QMX Focus): develop optimized kernels (GEMM, convolution, attention) for QMX and integrate with ML frameworks.
• Benchmarking Performance Engineering: establish baselines and track improvements across hardware generations.

Skills

C/C++ (mandatory)

Performance profiling

Benchmarking

Optimization

Machine Learning fundamentals

Computer Architecture

Tools

QEMU simulators

LLVM toolchain

Job description

Job Summary

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.

CPU Software Hardware Co-Design Engineer (ML Systems)

Location: Bangalore (or relevant)

Levels: Engineer / Senior Engineer / Staff / Principal Engineer

Role Overview

We are building a high-impact team at the intersection of CPU architecture, machine learning workloads, and system-level performance optimization. This role focuses on CPU softwarehardware co-design for next-generation QMX architectures, including workload characterization, simulation, kernel optimization, and driving architectural insights for future CPU designs. The ideal candidate will work across the full stackfrom ML models to low-level kernels to architectural feedbackenabling efficient execution of ML workloads on CPU platforms.

Key Responsibilities

• ML Workload Identification Characterization
  • Identify and prioritize critical ML use cases and models for CPU-centric execution (LLMs, vision, speech, recommender systems, etc.)
  • Analyze workload characteristics including:
    • Compute intensity
    • Memory bandwidth and cache behavior
    • Parallelism and dataflow patterns
• Simulation Trace Generation
  • Generate detailed execution traces for ML workloads using QEMU or equivalent simulators
  • Develop tooling to:
    • Capture instruction-level execution behavior
    • Extract performance counters and bottlenecks
  • Enable accurate modeling of workload behavior for architectural exploration
• Bottleneck Analysis Performance Optimization
  • Identify system bottlenecks across:
    • CPU pipelines
    • Memory hierarchy
    • Instruction utilization
  • Optimize critical hotspots through:
    • Kernel-level tuning
    • Algorithmic improvements
    • Data layout and memory optimizations
  • Drive measurable improvements in workload performance
• SoftwareHardware Co-Design
  • Collaborate with CPU architecture and design teams to:
    • Provide data-driven insights from real workloads
    • Identify inefficiencies and propose architectural enhancements
  • Influence next-generation CPU features in:
    • Compute units
    • Vector/SIMD extensions (e.g., QMX)
    • Memory subsystems
• ML Kernel Library Development (QMX Focus)
  • Design and implement highly optimized ML kernels and libraries for QMX architecture
  • Develop kernels for:
    • GEMM, convolution, attention
  • Enable integration with:
    • Open-source ML frameworks (e.g., PyTorch, ONNX, XNNPACK, MLAS)
  • Apply advanced optimizations:
    • SIMD/vectorization
    • Cache-aware execution
    • Parallel execution strategies
• Benchmarking Performance Engineering
  • Optimize CPU-centric ML benchmarks such as:
    • Geekbench AI
    • Internal benchmarking suites
  • Establish performance baselines and track improvements across hardware generations
  • Perform competitive analysis and performance positioning

Required Qualifications

• Strong background in:
  • Computer Architecture / Systems Programming
  • Machine Learning fundamentals
• Proficiency in:
  • C/C++ (mandatory)
• Experience with:
  • Performance profiling, benchmarking, and optimization

Preferred Qualifications

• Experience with:
  • QEMU or equivalent simulators
  • ML kernel development (GEMM, convolution, attention)
• Knowledge of:
  • CPU architecture (pipelines, caching, SIMD/vector extensions such as NEON, SVE, QMX)
• Familiarity with:
  • ML frameworks and inference stacks
• Experience with low-level optimization:
  • Intrinsics, assembly, memory and cache tuning