Design and optimize modem software for embedded systems, focusing on performance analysis, architectural trade-offs, and real-world workload optimization. Conduct pre-silicon evaluations, profile silicon behavior, and develop debugging and validation tools.… Apply data-driven analysis and machine-learning techniques to identify bottlenecks across multiple chipset generations and implement solutions through software optimization, cache tuning, and memory management.
Qualcomm seeks a Windows Performance Engineer to analyze and optimize software running on Windows for Snapdragon devices, working across multiple software layers including the OS kernel, compilers, drivers, and CPU microarchitecture. The role requires implementing performance optimizations while managing power consumption trade-offs, developing analysis tools, and collaborating with internal teams and external partners.… The ideal candidate will have deep expertise in C/C++, ARM assembly, CPU and memory architecture, and experience with Windows performance profiling tools like WPA.
Lead a machine learning engineering team designing Visual Language Action Models, Vision Language Models, and Large Language Models for autonomous driving and infotainment on Qualcomm's Snapdragon Ride platform. Optimize deep networks for accuracy-latency trade-offs on resource-constrained edge devices, focusing on low-level perception, end-to-end autonomous driving (L2/L3 ADAS), and multi-modal sensor fusion.… Drive cross-functional collaboration with automotive OEMs and internal Qualcomm teams while building a world-class AI/deep learning engineering organization. Requires 6–8+ years of systems engineering or machine learning experience (depending on degree level), with hands-on expertise in deep learning network design, quantization, and deployment on edge AI accelerators.
Staff-level machine learning software engineer responsible for designing, implementing, and optimizing ML software for embedded systems including mobile, edge, auto, and IoT products running on ARM, DSP, and GPU processors. Primary responsibilities include developing and optimizing ML kernels and frameworks (TensorFlow, PyTorch) for efficient hardware execution, implementing performance-critical software in C++/Python, and collaborating with hardware teams on joint design and optimization.… Will lead complex projects involving integration, testing, and tool development for embedded ML subsystems, coordinate cross-team dependencies, and contribute to design reviews and technical planning.
Design, implement, and verify machine learning software for embedded ARM processors, DSPs, and GPUs in mobile, edge, automotive, and IoT products. Optimize ML kernels, frameworks (TensorFlow, PyTorch), and compilers to leverage specific hardware capabilities; develop in C++, C, or Python with focus on performance tuning and integration testing.… Collaborate with hardware teams on joint design/development, coordinate dependencies across teams, and contribute to design reviews and project meetings.
Seeking a senior GPU compiler developer to design and implement compiler software architecture, pipelines, optimizations, and transformations for GPU platforms. The role requires collaborating with driver and hardware teams to implement new API and hardware features, improve performance and power consumption, and debug code generation issues.… The ideal candidate has 10+ years of compiler development experience, strong C/C++ expertise, deep knowledge of LLVM and compiler optimization techniques, and familiarity with GPU architecture and SIMD.
Qualcomm seeks an experienced Windows Performance Engineer to analyze and optimize software running on Windows on Snapdragon devices across multiple system layers—OS, kernel, compiler, drivers, assembly, and CPU/SoC architecture. The role involves deep performance analysis of benchmarks and applications, implementing software optimizations to balance performance and power consumption, developing analysis tools, and collaborating with architects and cross-functional teams.… The engineer will act as a technical lead, own project outcomes, and drive optimization strategies for next-generation Windows on Snapdragon desktop devices. Strong technical credibility, self-management, and communication skills are essential.
Design, implement, and verify machine learning software for embedded systems running on ARM processors, DSPs, and GPUs in mobile, edge, automotive, and IoT products. Develop optimized ML kernels, compilers, and tools; optimize ML frameworks like TensorFlow and PyTorch for efficient hardware execution.… Perform integration, testing, and performance optimization of embedded software subsystems. Collaborate with hardware teams on joint design and development, coordinate cross-team dependencies, and contribute to design reviews.
AMD seeks a Principal Compiler Architect to lead the design and optimization of LLVM-based compilers for AMD GPUs, focusing on performance improvements for ML frameworks and HPC applications. The role involves working with architecture specialists on hardware bring-ups, debugging compiler issues, and developing groundbreaking compilation technologies for current and future GPU hardware.… The candidate will apply data-driven optimization strategies, stay current with hardware and software trends, and collaborate across teams to enhance compiler support for ML and HPC workloads. Required expertise includes strong C/C++ programming, understanding of GPU execution models, and ideally a track record of open-source LLVM contributions.
As a Senior Systems Engineer for Data Center AI at Qualcomm, you will research, develop, optimize, and validate AI/ML solutions that integrate Qualcomm's hardware accelerators with software and ecosystem to deliver high-performance inference in datacenter environments. You will design and deploy Gen AI and LLM applications, implement fine-tuning and distillation techniques, perform model benchmarking, and drive system-level architecture decisions.… You will collaborate across functional teams to meet system-level requirements while staying current with advances in AI/ML models and hardware. Required skills include strong Python proficiency, expertise in ML frameworks (PyTorch, TensorFlow), deep understanding of ML deployment and system performance profiling, and experience with parallel computing.