{"id":3424069,"url":"https://alion.io/job/amd-senior-gpu-performance-engineer-ai-workloads","title":"Senior GPU Performance Engineer - AI Workloads","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":"B","score":78,"open_postings":167,"ghost_share":0,"stale_share":0.898,"repost_share":0,"time_to_fill_p50_days":34,"computed_at":"2026-10-30T05:48:23Z"}},"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":173000,"max_usd":332000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"JAX","optional":false},{"name":"Linux","optional":false},{"name":"Megatron-LM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NCCL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"ROCm","optional":false}],"status":"live","first_seen_at":"2026-10-28T19:44:00Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-30T08:25:49Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"ADVANCE YOUR CAREER. ADVANCE THE WORLD.\nAt AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.\nWhether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger - technology that moves the world forward. Join us and, together, we’ll advance your career.\nAbout the Role\nWe are seeking a GPU Performance Engineer to optimize AI workloads and guide the evolution of next-generation AMD Instinct GPU architectures. In this role, you will work across the software and hardware stack to perform deep GPU kernel-level performance analysis, identify microarchitectural bottlenecks, and drive low-level kernel optimizations for foundation model workloads on large-scale GPU systems. You will collaborate with kernel, framework, distributed systems, compiler/runtime, and hardware architecture teams to ensure our GPUs deliver industry-leading AI performance today while shaping the designs of tomorrow.\nKey Responsibilities\nProfile and optimize large-scale AI workloads, including transformers, multimodal models, diffusion models, and recommender systems, across multi-node, multi-GPU systems.\nPerform deep GPU kernel-level analysis to identify bottlenecks in compute pipelines, memory hierarchy, instruction execution, synchronization, and data movement.\nRoot-cause performance gaps using GPU performance counters, thread traces, ISA/assembly analysis, and targeted microbenchmarks, and deliver low-level kernel optimizations.\nCollaborate with kernel, compiler, runtime, framework, and distributed systems teams to improve kernel performance, scheduling, memory utilization, and system-level efficiency.\nDevelop and maintain benchmarks, microbenchmarks, and traces representative of foundation model and broader AI workloads.\nProvide kernel- and microarchitecture-level performance insights to AMD Instinct GPU architecture teams, informing hardware/software co-design decisions for future architectures.\nPresent findings to cross-functional teams and leadership, shaping both software and hardware roadmaps.\n\nMinimum Qualifications\nMS or PhD in Computer Science, Computer Engineering, or a related technical field.\nStrong hands-on experience in GPU kernel-level performance analysis and low-level optimization using CUDA, HIP/ROCm, or equivalent technologies.\nDeep understanding of GPU microarchitecture, including execution pipelines, SIMD/SIMT scheduling, registers, memory hierarchy, caches, and interconnects.\nExperience using performance counters, thread traces, profilers, and ISA/assembly analysis to root-cause GPU kernel performance bottlenecks.\nHands-on experience optimizing performance-critical GPU kernels and developing targeted microbenchmarks or reproducer kernels.\nProficiency in C++ and GPU kernel programming, with Python experience for performance analysis and automation.\nAdvanced Linux OS, container technologies such as Docker, and Git/GitHub skills.\nFamiliarity with AI workloads, AI frameworks, distributed computing, and communication libraries, such as PyTorch, JAX, Megatron-LM, NCCL/RCCL, and MPI.\n\nPreferred Qualifications\nStrong track record of delivering GPU kernel performance improvements through low-level hardware/software analysis and optimization.\nExperience working across kernel, compiler/runtime, framework, distributed systems, and GPU architecture teams to resolve complex performance bottlenecks.\nExperience analyzing large-scale AI workloads and translating workload-level performance gaps into actionable kernel, software-stack, or microarchitecture improvements.\nThis role is not eligible for visa sponsorship.\n#LI-RL1\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.\nAbout the Role\nWe are seeking a GPU Performance Engineer to optimize AI workloads and guide the evolution of next-generation AMD Instinct GPU architectures. In this role, you will work across the software and hardware stack to perform deep GPU kernel-level performance analysis, identify microarchitectural bottlenecks, and drive low-level kernel optimizations for foundation model workloads on large-scale GPU systems. You will collaborate with kernel, framework, distributed systems, compiler/runtime, and hardware architecture teams to ensure our GPUs deliver industry-leading AI performance today while shaping the designs of tomorrow.\nKey Responsibilities\nProfile and optimize large-scale AI workloads, including transformers, multimodal models, diffusion models, and recommender systems, across multi-node, multi-GPU systems.\nPerform deep GPU kernel-level analysis to identify bottlenecks in compute pipelines, memory hierarchy, instruction execution, synchronization, and data movement.\nRoot-cause performance gaps using GPU performance counters, thread traces, ISA/assembly analysis, and targeted microbenchmarks, and deliver low-level kernel optimizations.\nCollaborate with kernel, compiler, runtime, framework, and distributed systems teams to improve kernel performance, scheduling, memory utilization, and system-level efficiency.\nDevelop and maintain benchmarks, microbenchmarks, and traces representative of foundation model and broader AI workloads.\nProvide kernel- and microarchitecture-level performance insights to AMD Instinct GPU architecture teams, informing hardware/software co-design decisions for future architectures.\nPresent findings to cross-functional teams and leadership, shaping both software and hardware roadmaps.\n\nMinimum Qualifications\nMS or PhD in Computer Science, Computer Engineering, or a related technical field.\nStrong hands-on experience in GPU kernel-level performance analysis and low-level optimization using CUDA, HIP/ROCm, or equivalent technologies.\nDeep understanding of GPU microarchitecture, including execution pipelines, SIMD/SIMT scheduling, registers, memory hierarchy, caches, and interconnects.\nExperience using performance counters, thread traces, profilers, and ISA/assembly analysis to root-cause GPU kernel performance bottlenecks.\nHands-on experience optimizing performance-critical GPU kernels and developing targeted microbenchmarks or reproducer kernels.\nProficiency in C++ and GPU kernel programming, with Python experience for performance analysis and automation.\nAdvanced Linux OS, container technologies such as Docker, and Git/GitHub skills.\nFamiliarity with AI workloads, AI frameworks, distributed computing, and communication libraries, such as PyTorch, JAX, Megatron-LM, NCCL/RCCL, and MPI.\n\nPreferred Qualifications\nStrong track record of delivering GPU kernel performance improvements through low-level hardware/software analysis and optimization.\nExperience working across kernel, compiler/runtime, framework, distributed systems, and GPU architecture teams to resolve complex performance bottlenecks.\nExperience analyzing large-scale AI workloads and translating workload-level performance gaps into actionable kernel, software-stack, or microarchitecture improvements.\nThis role is not eligible for visa sponsorship.\n#LI-RL1\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.","description_format":"text","description_chars":9072,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Processors, MCUs & AI Chips","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-28T21:46:35Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":1,"expected_fill_days":34,"reasons":["conf:1","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-30T05:48:23Z"},"pay":null,"html_url":"https://alion.io/job/amd-senior-gpu-performance-engineer-ai-workloads","json_url":"https://alion.io/job/amd-senior-gpu-performance-engineer-ai-workloads.json","meta":{"generated_at":"2026-10-30T11:52:03Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":17071,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-31T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":93},"rest":"https://alion.io/mcp/rest/get_company?id=93"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Famd-senior-gpu-performance-engineer-ai-workloads"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Famd-senior-gpu-performance-engineer-ai-workloads"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Famd-senior-gpu-performance-engineer-ai-workloads"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/amd-senior-gpu-performance-engineer-ai-workloads\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Famd-senior-gpu-performance-engineer-ai-workloads"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3424069}},{"tool":"search_jobs","arguments":{"company":"amd.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3424069},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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