{"id":2912048,"url":"https://alion.io/job/amd-sr-software-development-engineer-gpu-kernel-development","title":"Sr. Software Development Engineer – GPU Kernel Development","company":{"id":93,"name":"AMD","domain":"amd.com","url":"https://alion.io/company/amd","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"A","score":97,"open_postings":17,"ghost_share":0,"stale_share":0.118,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-11-06T05:58:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":169000,"max_usd":325000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Linux","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"CUDA","optional":true},{"name":"CUTLASS","optional":true},{"name":"LLVM","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"ROCm","optional":true},{"name":"Triton","optional":true}],"status":"closed","first_seen_at":"2026-06-29T14:52:00Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T01:47:01Z","board_verified":false,"closed_at":"2026-11-04T01:47:01Z","days_open":127,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":124},"description":"WHAT YOU DO AT AMD CHANGES EVERYTHING\nAt AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gamingand embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuityand a shared passion to create something extraordinary. When you join AMD, you’lldiscover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.Together, we advance your career.\nTHE ROLE:\nAs a core member of the team, you will play a pivotal role in optimizingand developing deep learning frameworks for AMD GPUs. Your expertisewill be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with both internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations, utilizingcutting-edgecompiler technologies and advanced engineering principles to drive continuous improvement.\nTHE PERSON:\nSeeking an Industry Leading Expert C++ developer with advanced technical and analytical skills in Linux environments. The ideal candidate will excel in providing technical leadership, guiding teams, and driving projects/initiatives independently. You will define goals, scope, and own development efforts while collaborating effectively within a high-performing team.\nKEY RESPONSIBILITIES:\nOptimizeDeep Learning Frameworks:Enhance and optimizeframeworks like TensorFlow and PyTorchfor AMD GPUs in open-source repositories.\nDevelop GPU Kernels: Create and optimizeGPU kernels to maximize performance for specific AI operations.\nDevelop & Optimize Models: Design and optimizedeep learning models specifically for AMD GPU performance.\nCollaborate with GPU Library Teams:Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs.\nCollaborate with Open-Source Maintainers:Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream.\nWork in Distributed Computing Environments:Optimizedeep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems.\nUtilize Cutting-Edge Compiler Tech:Leverageadvanced compiler technologies to improve deep learning performance.\nOptimizeDeep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers.\nSoftware Engineering Best Practices:Apply sound engineering principles to ensure robust, maintainable solutions.\nLead, Guide& Mentor: Provide strategic direction and mentorship to junior team members, fostering growth and collaboration through code reviews, knowledge sharing, and technical guidance.\nPREFERRED EXPERIENCE:\nGPU Kernel Development & Optimization:Deep expertisein designing and optimizingGPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations, leveragingtools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance.\nDeep Learning Integration:Proven ability and experience to integrate GPU-accelerated computeinto ML frameworks (e.g., PyTorch, TensorFlow), with a focus on throughput, scalability, and efficient execution for training and inference workloads.\nSoftware EngineeringExcellence:Advanced proficiencyin Python and C++ with deep experience in performance tuning, debugging, and robust test design, ensuring reliable, maintainable, high-performance codebases.\nHigh-Performance Computing:Broad and indepthexperience with large-scale, heterogeneous computeenvironments; adept at optimizingAI workloads for performance, efficiency, and resource utilizationacross clusters.\nCompiler Optimization: Thorough and detailedunderstanding of compiler internals, LLVM, and ROCm, with the ability to drive system-level optimizations from source to machine code.\nACADEMIC CREDENTIALS:\nMaster’s and/ PhD degreein Computer Science, Computer Engineering, Electrical Engineering, or a relatedfield.\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.\nTHE ROLE:\nAs a core member of the team, you will play a pivotal role in optimizingand developing deep learning frameworks for AMD GPUs. Your expertisewill be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with both internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations, utilizingcutting-edgecompiler technologies and advanced engineering principles to drive continuous improvement.\nTHE PERSON:\nSeeking an Industry Leading Expert C++ developer with advanced technical and analytical skills in Linux environments. The ideal candidate will excel in providing technical leadership, guiding teams, and driving projects/initiatives independently. You will define goals, scope, and own development efforts while collaborating effectively within a high-performing team.\nKEY RESPONSIBILITIES:\nOptimizeDeep Learning Frameworks:Enhance and optimizeframeworks like TensorFlow and PyTorchfor AMD GPUs in open-source repositories.\nDevelop GPU Kernels: Create and optimizeGPU kernels to maximize performance for specific AI operations.\nDevelop & Optimize Models: Design and optimizedeep learning models specifically for AMD GPU performance.\nCollaborate with GPU Library Teams:Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs.\nCollaborate with Open-Source Maintainers:Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream.\nWork in Distributed Computing Environments:Optimizedeep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems.\nUtilize Cutting-Edge Compiler Tech:Leverageadvanced compiler technologies to improve deep learning performance.\nOptimizeDeep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers.\nSoftware Engineering Best Practices:Apply sound engineering principles to ensure robust, maintainable solutions.\nLead, Guide& Mentor: Provide strategic direction and mentorship to junior team members, fostering growth and collaboration through code reviews, knowledge sharing, and technical guidance.\nPREFERRED EXPERIENCE:\nGPU Kernel Development & Optimization:Deep expertisein designing and optimizingGPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations, leveragingtools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance.\nDeep Learning Integration:Proven ability and experience to integrate GPU-accelerated computeinto ML frameworks (e.g., PyTorch, TensorFlow), with a focus on throughput, scalability, and efficient execution for training and inference workloads.\nSoftware EngineeringExcellence:Advanced proficiencyin Python and C++ with deep experience in performance tuning, debugging, and robust test design, ensuring reliable, maintainable, high-performance codebases.\nHigh-Performance Computing:Broad and indepthexperience with large-scale, heterogeneous computeenvironments; adept at optimizingAI workloads for performance, efficiency, and resource utilizationacross clusters.\nCompiler Optimization: Thorough and detailedunderstanding of compiler internals, LLVM, and ROCm, with the ability to drive system-level optimizations from source to machine code.\nACADEMIC CREDENTIALS:\nMaster’s and/ PhD degreein Computer Science, Computer Engineering, Electrical Engineering, or a relatedfield.\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. 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