{"id":3796315,"url":"https://alion.io/job/amd-ai-power-performance-engineer","title":"AI Power & Performance Engineer","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Bash","optional":false},{"name":"Linux","optional":false},{"name":"llama.cpp","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"ROCm","optional":false},{"name":"TensorFlow","optional":false},{"name":"vLLM","optional":false},{"name":"Docker","optional":true},{"name":"LLM","optional":true},{"name":"Machine Learning","optional":true},{"name":"Vitis","optional":true}],"status":"live","first_seen_at":"2026-11-05T07:38:00Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-06T09:08:37Z","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.\nAI Power & Performance Engineer\nRole Overview\nWe are seeking an experienced AI Power & Performance Engineer to join our AI System PnP team. The candidate will evaluate, benchmark, profile, and optimize AI inference workloads across modern CPU, GPU, APU, and heterogeneous computing platforms.\nKey Responsibilities\nBenchmark and characterize AI inference workloads using PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, and related technologies.\nAnalyze latency, throughput, memory utilization, power consumption, and performance per watt.\nProfile workloads and identify bottlenecks across AI frameworks, runtimes, operating systems, memory subsystems, and hardware.\nOptimize workload performance through quantization, graph optimization, kernel tuning, memory optimization, and heterogeneous compute utilization.\nConduct competitive benchmarking across AMD and competing CPU, GPU, APU, and AI accelerator platforms.\nAutomate benchmark execution, data collection, regression analysis, and results visualization.\nConvert benchmarking results into actionable recommendations for software, hardware, product, and business teams.\nCollaborate with architects, framework, runtime, driver, firmware, and system software teams to resolve performance issues.\nRequired Skills & Experience\n5 to 10 years of relevant experience in AI performance engineering, system performance analysis, workload optimization, or benchmarking.\nHands-on experience benchmarking AI inference workloads on CPU, GPU, APU, or NPU platforms.\nStrong experience with PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, or similar frameworks and runtimes.\nStrong Linux expertise with experience in performance profiling, workload tracing, automation, and system-level debugging.\nExperience with profiling tools such as Linux perf, AMD uProf, ROCm Profiler, Nsight Systems, VTune, Perfetto, or equivalent tools.\nGood understanding of CPU/GPU architecture, memory hierarchy, power and thermal behavior, and performance trade-offs.\nProficiency in Python and Bash for automation, data analysis, and reporting.\nAbility to communicate complex performance data through clear technical reports, dashboards, and recommendations.\nPreferred Qualifications\nExperience with ROCm, Ryzen AI Software, Vitis AI, MIGraphX, or related AI technologies.\nKnowledge of model quantization, mixed-precision inference, graph optimization, and LLM-serving techniques.\nExperience with MLPerf Inference, competitive benchmarking, Docker, virtualization, or post-silicon performance validation.\nEducation\nBachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related field.\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.\nAI Power & Performance Engineer\nRole Overview\nWe are seeking an experienced AI Power & Performance Engineer to join our AI System PnP team. The candidate will evaluate, benchmark, profile, and optimize AI inference workloads across modern CPU, GPU, APU, and heterogeneous computing platforms.\nKey Responsibilities\nBenchmark and characterize AI inference workloads using PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, and related technologies.\nAnalyze latency, throughput, memory utilization, power consumption, and performance per watt.\nProfile workloads and identify bottlenecks across AI frameworks, runtimes, operating systems, memory subsystems, and hardware.\nOptimize workload performance through quantization, graph optimization, kernel tuning, memory optimization, and heterogeneous compute utilization.\nConduct competitive benchmarking across AMD and competing CPU, GPU, APU, and AI accelerator platforms.\nAutomate benchmark execution, data collection, regression analysis, and results visualization.\nConvert benchmarking results into actionable recommendations for software, hardware, product, and business teams.\nCollaborate with architects, framework, runtime, driver, firmware, and system software teams to resolve performance issues.\nRequired Skills & Experience\n5 to 10 years of relevant experience in AI performance engineering, system performance analysis, workload optimization, or benchmarking.\nHands-on experience benchmarking AI inference workloads on CPU, GPU, APU, or NPU platforms.\nStrong experience with PyTorch, ONNX Runtime, vLLM, llama.cpp, TensorFlow, or similar frameworks and runtimes.\nStrong Linux expertise with experience in performance profiling, workload tracing, automation, and system-level debugging.\nExperience with profiling tools such as Linux perf, AMD uProf, ROCm Profiler, Nsight Systems, VTune, Perfetto, or equivalent tools.\nGood understanding of CPU/GPU architecture, memory hierarchy, power and thermal behavior, and performance trade-offs.\nProficiency in Python and Bash for automation, data analysis, and reporting.\nAbility to communicate complex performance data through clear technical reports, dashboards, and recommendations.\nPreferred Qualifications\nExperience with ROCm, Ryzen AI Software, Vitis AI, MIGraphX, or related AI technologies.\nKnowledge of model quantization, mixed-precision inference, graph optimization, and LLM-serving techniques.\nExperience with MLPerf Inference, competitive benchmarking, Docker, virtualization, or post-silicon performance validation.\nEducation\nBachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related field.\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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