{"id":2912274,"url":"https://alion.io/job/amd-principal-senior-gpu-sw-performance-engineer-post-training","title":"Principal / Senior GPU SW Performance Engineer — Post‑Training","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":80,"open_postings":157,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":193000,"max_usd":395000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":730},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"Post-training","optional":false},{"name":"ROCm","optional":false},{"name":"C++","optional":true},{"name":"FSDP","optional":true},{"name":"LoRA","optional":true},{"name":"PEFT","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"SFT","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-03-25T19:28:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-22T11:40:18Z","board_verified":true,"closed_at":null,"days_open":210,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":210},"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:\nDrive the performance of post-training workloads on AMD Instinct™ GPUs. You’ll work across kernels, distributed training, and framework integrations to deliver fast, stable, and reproducible training pipelines on ROCm.\nTHE PERSON:\nThe ideal candidate is passionate about software engineering and the craft of training performance. You lead sophisticated cross-stack issues-spanning data loaders, kernels, distributed training, and compilers-to clear resolution. You communicate crisply and collaborate effectively with framework, compiler, kernel, and model teams across AMD, driving measurable improvements with rigor, ownership, and reproducibility.\nKEY RESPONSIBILITIES:\nLead performance for finetuning and RL training solutions on AMD GPUs.\nImprove throughput, memory efficiency, and stability across data, model, and optimizer steps.\nOptimize multi-GPU/multi-node training and communication patterns.\nContribute efficient kernels/ops and targeted graph-level optimizations.\nProfile, diagnose, and resolve bottlenecks using standard tooling; prevent regressions in CI.\nShip reproducible pipelines and documentation adopted by internal teams and external developers.\nCollaborate with framework, compiler, and model teams to land durable improvements.\n\nPREFERRED EXPERIENCE:\nProven GPU performance engineering for deep learning (ROCm/HIP, Triton, or similar).\nHands-on with SFT. LoRA and RL-based training at scale.\nStrong PyTorch experience (torch.distributed, FSDP/ZeRO or equivalent).\nProficient in Python and C++; comfortable reading/writing kernels when needed.\nExperience with distributed systems and collective communication libraries.\nTrack record of turning profiles into fixes, upstreaming changes, and documenting results.\nACADEMIC CREDENTIALS:\nB.S./M.S./Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent\nLOCATION:\nSan Jose, CA preferred. Other US based locations may be considered.\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:\nDrive the performance of post-training workloads on AMD Instinct™ GPUs. You’ll work across kernels, distributed training, and framework integrations to deliver fast, stable, and reproducible training pipelines on ROCm.\nTHE PERSON:\nThe ideal candidate is passionate about software engineering and the craft of training performance. You lead sophisticated cross-stack issues-spanning data loaders, kernels, distributed training, and compilers-to clear resolution. You communicate crisply and collaborate effectively with framework, compiler, kernel, and model teams across AMD, driving measurable improvements with rigor, ownership, and reproducibility.\nKEY RESPONSIBILITIES:\nLead performance for finetuning and RL training solutions on AMD GPUs.\nImprove throughput, memory efficiency, and stability across data, model, and optimizer steps.\nOptimize multi-GPU/multi-node training and communication patterns.\nContribute efficient kernels/ops and targeted graph-level optimizations.\nProfile, diagnose, and resolve bottlenecks using standard tooling; prevent regressions in CI.\nShip reproducible pipelines and documentation adopted by internal teams and external developers.\nCollaborate with framework, compiler, and model teams to land durable improvements.\n\nPREFERRED EXPERIENCE:\nProven GPU performance engineering for deep learning (ROCm/HIP, Triton, or similar).\nHands-on with SFT. LoRA and RL-based training at scale.\nStrong PyTorch experience (torch.distributed, FSDP/ZeRO or equivalent).\nProficient in Python and C++; comfortable reading/writing kernels when needed.\nExperience with distributed systems and collective communication libraries.\nTrack record of turning profiles into fixes, upstreaming changes, and documenting results.\nACADEMIC CREDENTIALS:\nB.S./M.S./Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent\nLOCATION:\nSan Jose, CA preferred. Other US based locations may be considered.\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":6527,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-20T09:52:16Z"}],"visa":[],"liveness":{"score":5,"band":"cold","label":"Long shot","p_open":1,"p_active":0.184,"p_room":0.28,"age_days":210,"expected_fill_days":15,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-22T06:10:10Z"},"pay":null,"html_url":"https://alion.io/job/amd-principal-senior-gpu-sw-performance-engineer-post-training","json_url":"https://alion.io/job/amd-principal-senior-gpu-sw-performance-engineer-post-training.json","meta":{"generated_at":"2026-10-22T12:22:40Z","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":10748,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-23T00:00:00Z"}},"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-principal-senior-gpu-sw-performance-engineer-post-training"},{"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-principal-senior-gpu-sw-performance-engineer-post-training"},{"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-principal-senior-gpu-sw-performance-engineer-post-training"},{"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-principal-senior-gpu-sw-performance-engineer-post-training\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Famd-principal-senior-gpu-sw-performance-engineer-post-training"}]}