CPU Software & Hardware Co-Design Engineer (ML Systems)
公司：高通技术，集团工作区：工程组，工程组 >软件工程总结：作为一个领先的技术创新者，高通推进了实现下一代体验的可能性的边界，并推动数字转型，以帮助创造更智能，互联的未来。作为高通软件工程师，你将设计，开发，创建，修改和验证嵌入式和云端软件，应用程序和/或专业化公用程序，这些项目启动最先进的世界级产品，满足并超越客户需求。高通软件工程师与系统，硬件，架构，测试工程师和其他团队合作设计系统级软件解决方案并获取性能要求和接口的信息。角色概述 我们正在建立一个高影响力的团队在 CPU 架构交叉点，机器学习工作负载和系统级绩效优化。这个职位侧重于 CPU 软件硬件共同设计下一代 QMX 架构，包括工作负载特征化，模拟，内核优化以及推动未来 CPU 设计的建筑见解。理想的候选人将在整个堆中工作，从 ML 模型到低级内核到架构反，从而使 ML 的工作负载能够在 CPU 平台上高效执行。关键责任 1.ML 工作负载识别和特征 ·确定并优先考虑关键的 ML 使用案例和基于 CPU 的执行模式 （LLMs,视觉，语音，推系统等）·分析包括：计算强度 Memory 带宽和缓存行为共性和数据流模式 2.模拟与追踪生成 ·利用 QEMU 或模拟器创建类似的 ML 工作负荷的详细执行痕迹 ·开发工具：捕获指令级执行行为 提取性能计数和瓶 ·实现对建筑探索工作负载行为的准确建模 3.瓶分析与性能优化 ·识别系统瓶在 CPU 管道中：记忆层次结构 Instruction 利用 ·通过：Kernel 级调整优化关键热点数据布局和内存优化 ·推动可测量的工作负载性能改善 4.软件硬件共设计 ·与架构和设计团队合作：从实际工作负载中提供基于数据的见解确定功能不足和一个 CPU
查看英文原文
Company:
Qualcomm Technologies, Inc.Job Area:
Engineering Group, Engineering Group > Software EngineeringGeneral 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.
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. 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 intensityMemory bandwidth and cache behaviorParallelism and dataflow patterns
2. Simulation & Trace Generation
- Generate detailed execution traces for ML workloads using QEMU or equivalent simulators
- Develop tooling to:Capture instruction-level execution behaviorExtract performance counters and bottlenecks
- Enable accurate modeling of workload behavior for architectural exploration
3. Bottleneck Analysis & Performance Optimization
- Identify system bottlenecks across:CPU pipelinesMemory hierarchyInstruction utilization
- Optimize critical hotspots through:Kernel-level tuningAlgorithmic improvementsData layout and memory optimizations
- Drive measurable improvements in workload performance
4. Software–Hardware Co-Design
- Collaborate with CPU architecture and design teams to:Provide data-driven insights from real workloadsIdentify inefficiencies and propose architectural enhancements
- Influence next-generation CPU features in:Compute unitsVector/SIMD extensions (e.g., QMX)Memory subsystems
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/vectorizationCache-aware executionParallel execution strategies
6. Benchmarking & Performance Engineering
- Optimize CPU-centric ML benchmarks such as:Geekbench AIInternal 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 ProgrammingMachine Learning fundamentals
- Proficiency in:C/C++ (mandatory)
- Experience with:Performance profiling, benchmarking, and optimization
Preferred Qualifications
- Experience with:QEMU or equivalent simulatorsML 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
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Software Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.
• 4+ years of work experience with Programming Language such as C, C++, Java, Python, etc.
Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may call Qualcomm's toll-free number foundhere. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
To all Staffing and Recruiting Agencies:Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
Pay rangeand Other Compensation & Benefits:
$177,300.00 - $265,900.00The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at thislink.
If you would like more information about this role, please contactQualcomm Careers.
Originally posted on Himalayas