Engineer/Senior Engineer- ML Libraries/ARM

Qualcomm; Bengaluru; On-site; INR 1,200,000 - 3,000,000; Full time

Job summary

Qualcomm India Private Limited is seeking a Software Engineer to join a high-impact team at the intersection of CPU architecture, ML workloads, and system-level performance optimization.

The role focuses on CPU software–hardware co-design for QMX architectures, including workload characterization, kernel optimization, and architectural insights for future CPU designs. Collaboration with architecture, systems, and AI teams is essential.

Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field with 2+ years of software engineering or related work experience.
• Master's degree in Engineering, Information Systems, Computer Science, or related field with 1+ year of software engineering or related work experience.
• PhD in Engineering, Information Systems, Computer Science, or related field.
• 2+ years of academic or work experience with programming languages such as C, C++, Java, Python, etc.

Responsibilities

• Identify and prioritize ML use cases for CPU-centric execution (LLMs, vision, speech, recommender systems).
• Analyze workload characteristics: compute intensity, memory bandwidth, cache behavior, parallelism, dataflow patterns.
• Generate detailed execution traces for ML workloads using QEMU or equivalent simulators.

Skills

Computer Architecture

C/C++

Performance profiling

Machine Learning fundamentals

Education

Bachelor's degree in Engineering/CS/IS

Master's degree in Engineering/CS/IS

PhD in Engineering/CS/IS

Tools

QEMU

Job description

Company:

Qualcomm India Private Limited

Job Area:

Engineering Group, Engineering Group > Software Engineering

General 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.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.
• Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.
• PhD in Engineering, Information Systems, Computer Science, or related field.
• 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Job Description: 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 software–hardware 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 stack—from ML models to low-level kernels to architectural feedback—enabling efficient execution of ML workloads on CPU platforms.

Key Responsibilities

1. 1. 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
2. 2. 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
3. 3. 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
4. 4. Software-Hardware 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
5. 5. ML Kernel & Library Development (QMX Focus)
   • Design and implement highly optimized ML kernels and libraries for QMX architecture
   • Develop kernels for:
     • GEMM, convolution, attention, activation functions, etc.
   • Enable integration with:
     • Open-source ML frameworks (e.g., PyTorch, ONNX, XNNPACK, MLAS)
   • Apply advanced optimizations:
     • SIMD/vectorization
     • Cache-aware execution
     • Parallel execution strategies
6. 6. 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

Why Join This Team

• Work on next-generation CPU architectures (QMX)
• Directly influence hardware design through real workload insights
• Solve end-to-end ML performance challenges (model - kernel - silicon)
• Collaborate with top architecture, systems, and AI teams
• High-impact role with visibility across product and research roadmaps

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