{"id":2912283,"url":"https://alion.io/job/amd-principal-software-engineer-pytorch-training-frameworks","title":"Principal Software Engineer – PyTorch Training Frameworks","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":77,"open_postings":170,"ghost_share":0,"stale_share":0.906,"repost_share":0,"time_to_fill_p50_days":32,"computed_at":"2026-10-29T05:49:05Z"}},"role":"Backend","role_family":"Backend","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":185000,"max_usd":369000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1231},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"FSDP","optional":false},{"name":"PyTorch","optional":false},{"name":"ROCm","optional":false},{"name":"C++","optional":true},{"name":"CUDA","optional":true},{"name":"Linux","optional":true},{"name":"NCCL","optional":true},{"name":"Python","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-01-30T23:57:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-29T10:15:06Z","board_verified":true,"closed_at":null,"days_open":271,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":271},"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:\nAMD is looking for a Principal-level PyTorch training framework expert to help drive performance, scalability, and correctness of large-scale AI training on AMD Instinct™ accelerators. You will work at the intersection of PyTorch internals, distributed training, and hardware-aware optimization, partnering closely with compiler, kernel, driver, and architecture teams to deliver industry-leading training performance and developer experience.\nTHE PERSON:\nThe ideal candidate is deeply hands-on with PyTorch training and thrives on solving complex systems problems (performance, scaling, memory efficiency, distributed communication). You bring strong technical leadership, can influence architecture across teams, and are comfortable driving ambiguity to crisp execution. You communicate clearly with both engineers and stakeholders and can represent AMD credibly in upstream/open-source discussions.\nKEY RESPONSIBILITIES:\nAct as a technical authority for PyTorch training at AMD, setting direction for performance, scalability, and reliabilityDrive optimization of key PyTorch training workloads (LLMs/foundation models) across single-node and multi-node systems\n\nImprove and debug training performance in areas such as DDP/FSDP, gradient checkpointing, mixed precision, memory planning, and communication/computation overlap\nPartner with ROCm compiler/runtime, kernel, and driver teams to resolve performance bottlenecks and correctness issues across the full stack\nContribute to and influence upstream PyTorch (design discussions, code contributions, performance fixes, CI/debug)\nDevelop and maintain representative training benchmarks, profiling workflows, and performance regression detection for key models\nLead deep-dive investigations of performance regressions and hard correctness issues; drive cross-team resolution to closure\nMentor engineers and raise the bar on framework-quality code, performance engineering practices, and technical rigor\nEngage with strategic customers/partners on training enablement, root-cause analysis, and best-practices for AMD platforms\nPREFERRED EXPERIENCE:\nDeep experience with PyTorch internals and training systems (Autograd, optimizers, dataloading, compilation paths, runtime behavior)\nStrong distributed training expertise: DDP, FSDP, tensor/pipeline parallel concepts, collectives (NCCL/RCCL), multi-node debugging\nProven track record in performance engineering (profiling, tracing, kernel/runtime analysis, memory optimization, scaling studies)\nStrong programming skills in Python and C/C++ (ability to land clean, maintainable changes in large codebases)\nFamiliarity with PyTorch ecosystem components such as TorchInductor / torch.compile, Triton, CUDA/HIP-style programming models, and performance tooling\nExperience working across OS/hardware boundaries in Linux-based environments (containers, CI, drivers/runtimes are a plus)\nClear technical communication: design docs, code reviews, stakeholder updates, and cross-team coordination\nDemonstrated ability to lead through influence (principal-level impact, mentoring, and architectural decision-making)\nACADEMIC CREDENTIALS:\nBachelor’s or Master'sdegree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent\nLOCATION:\nSan Jose, Seattle or Austin are preferred.\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:\nAMD is looking for a Principal-level PyTorch training framework expert to help drive performance, scalability, and correctness of large-scale AI training on AMD Instinct™ accelerators. You will work at the intersection of PyTorch internals, distributed training, and hardware-aware optimization, partnering closely with compiler, kernel, driver, and architecture teams to deliver industry-leading training performance and developer experience.\nTHE PERSON:\nThe ideal candidate is deeply hands-on with PyTorch training and thrives on solving complex systems problems (performance, scaling, memory efficiency, distributed communication). You bring strong technical leadership, can influence architecture across teams, and are comfortable driving ambiguity to crisp execution. You communicate clearly with both engineers and stakeholders and can represent AMD credibly in upstream/open-source discussions.\nKEY RESPONSIBILITIES:\nAct as a technical authority for PyTorch training at AMD, setting direction for performance, scalability, and reliabilityDrive optimization of key PyTorch training workloads (LLMs/foundation models) across single-node and multi-node systems\n\nImprove and debug training performance in areas such as DDP/FSDP, gradient checkpointing, mixed precision, memory planning, and communication/computation overlap\nPartner with ROCm compiler/runtime, kernel, and driver teams to resolve performance bottlenecks and correctness issues across the full stack\nContribute to and influence upstream PyTorch (design discussions, code contributions, performance fixes, CI/debug)\nDevelop and maintain representative training benchmarks, profiling workflows, and performance regression detection for key models\nLead deep-dive investigations of performance regressions and hard correctness issues; drive cross-team resolution to closure\nMentor engineers and raise the bar on framework-quality code, performance engineering practices, and technical rigor\nEngage with strategic customers/partners on training enablement, root-cause analysis, and best-practices for AMD platforms\nPREFERRED EXPERIENCE:\nDeep experience with PyTorch internals and training systems (Autograd, optimizers, dataloading, compilation paths, runtime behavior)\nStrong distributed training expertise: DDP, FSDP, tensor/pipeline parallel concepts, collectives (NCCL/RCCL), multi-node debugging\nProven track record in performance engineering (profiling, tracing, kernel/runtime analysis, memory optimization, scaling studies)\nStrong programming skills in Python and C/C++ (ability to land clean, maintainable changes in large codebases)\nFamiliarity with PyTorch ecosystem components such as TorchInductor / torch.compile, Triton, CUDA/HIP-style programming models, and performance tooling\nExperience working across OS/hardware boundaries in Linux-based environments (containers, CI, drivers/runtimes are a plus)\nClear technical communication: design docs, code reviews, stakeholder updates, and cross-team coordination\nDemonstrated ability to lead through influence (principal-level impact, mentoring, and architectural decision-making)\nACADEMIC CREDENTIALS:\nBachelor’s or Master'sdegree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent\nLOCATION:\nSan Jose, Seattle or Austin are preferred.\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":9245,"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":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.198,"p_room":0.28,"age_days":271,"expected_fill_days":32,"reasons":["conf:3","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-29T05:49:05Z"},"pay":null,"html_url":"https://alion.io/job/amd-principal-software-engineer-pytorch-training-frameworks","json_url":"https://alion.io/job/amd-principal-software-engineer-pytorch-training-frameworks.json","meta":{"generated_at":"2026-10-29T13:24:56Z","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":20137,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-30T00:00:00Z"}},"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-software-engineer-pytorch-training-frameworks"},{"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-software-engineer-pytorch-training-frameworks"},{"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-software-engineer-pytorch-training-frameworks"},{"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-software-engineer-pytorch-training-frameworks\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Famd-principal-software-engineer-pytorch-training-frameworks"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":2912283}},{"tool":"search_jobs","arguments":{"company":"amd.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":2912283},"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. Docs: https://alion.io/developers"}}