{"id":2284355,"url":"https://alion.io/job/intel-corporation-ai-gpu-arch-perf-analysis-intern","title":"AI GPU Arch Perf Analysis Intern","company":{"id":35,"name":"Intel","domain":"intel.com","url":"https://alion.io/company/intel","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":98,"ghost_share":0.02,"stale_share":0.571,"repost_share":0.041,"time_to_fill_p50_days":27,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Beijing, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16500,"max_usd":33000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":710},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true},{"name":"OpenCL","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-10-09T00:00:00Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-14T14:33:55Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"Job Details:\nJob Description:\nAs an AI Architecture Performance Analysis Graduate Intern, you will join Intel's GPU Compute Architecture team and contribute to core GPU kernel perf analysis using real AI workloads.Your work will directly support hardware/software co design and help analyze and shape the performance of next generation Intel GPU and AI accelerator platforms, while giving you hands on exposure to GPU architecture and low level performance engineering.\nKey Responsibilities\nAnalyze and optimize core GPU compute kernels for AI and numerical workloads (e.g., GEMM, Attention, operator fusion).\nReproduce representative AI inference and training workloads for GPU IP validation.\nPerform GPU performance profiling and analysis to identify compute, memory, and pipeline bottlenecks.\nBuild performance profiles and models to understand architecture level performance behavior.\nProvide workload and kernel level insights to support GPU architecture design and HW/SW co design efforts.Qualifications:\nMinimum Qualifications\nCurrently pursuing a Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.\nProficiency in Python for analysis, experimentation, or tooling.\nSolid understanding of AI fundamentals, including common models and algorithms.\nStrong interest in GPU architecture, GPU programming, parallel computing, and performance optimization.\nBasic knowledge of computer systems, such as CPU/GPU architecture, memory systems, and performance analysis.\nPreferred Qualifications\nExperience with GPU kernels or programming models (e.g., CUDA, OpenCL, SYCL, Triton).\nExposure to performance optimization, compiler, or parallel computing coursework, research, or internships.\nStrong analytical and problem solving skills, with the ability to reason from profiling data.\nInterest in AI systems and infrastructure, beyond model level development.\n• Ability to work effectively in a collaborative, cross functional engineering environment.\nJob Type:\nStudent / InternShift:\nShift 1 (China)Primary Location:\nPRC, BeijingAdditional Locations:\nPosting Statement:\nAll qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of Trust\nN/AWork Model for this Role\nThis role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.*\nADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. 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