{"id":3168407,"url":"https://alion.io/job/intel-ai-system-performance-engineer","title":"AI System Performance Engineer","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":88,"ghost_share":0.034,"stale_share":0.523,"repost_share":0.045,"time_to_fill_p50_days":30,"computed_at":"2026-10-24T06:02:35Z"}},"role":"DevOps","role_family":"DevOps","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","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":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DeepSeek","optional":false},{"name":"LLM","optional":false},{"name":"Mixture of Experts","optional":false},{"name":"Python","optional":false},{"name":"Qwen","optional":false},{"name":"Transformers","optional":false},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"GitHub","optional":true},{"name":"KV Cache","optional":true},{"name":"Quantization","optional":true},{"name":"SGLang","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-22T00:00:00Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-10-24T03:51:18Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Job Details:\nJob Description:\nAbout the Role\nWe are looking for a talented and motivated AI System Performance Engineer. The role builds a strong understanding of AI training and inference systems and helps the team develop analytical models that project end-to-end system performance. Working across serving strategies, parallelism, collective communication, and interconnect behavior, the candidate uses these models to locate the architectural bottlenecks that limit performance and to recommend optimal system configurations for Intel architecture. A self-driven, hands-on learning by doing mindset and the ability to pick up unfamiliar workloads, tools, and architectures quickly are essential.\nKey Responsibilities\nEnable new AI workloads in analytical simulators, and model emerging multi-GPU deployment, parallelization, and communication strategies as simulator capabilities.\nBuild analytical models of newly proposed GPU architectures - GPU core, memory hierarchy, and training/inference deployment scenarios - and produce performance estimates that expose architectural bottlenecks and drive improvement recommendations.\nIntegrate and modify open-source simulators or analytical models for Intel-specific architecture.\nPerform what-if analysis by sweeping core count, memory/cache capacity and bandwidth, fabric bandwidth, GPU interconnect, and deployment options; deliver optimization and optimal architecture recommendations.\nQualifications:\nRequired Qualifications\nBTech or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.\nCollege graduate or 1+ years of experience in AI workload and GPU architecture modelling/simulation or a similar field.\nStrong proficiency in Python, with the ability to build modular, maintainable analytical models and simulation frameworks.\nIn-depth understanding of computer architecture: GPU/CPU, ALU/SM core, cache, and different memory types and hierarchy.\nIn-depth understanding of LLM AI workloads (Transformer, MoE, Attention, MLA - LLaMA, DeepSeek, Qwen, and robotic workloads) and kernel internals. Good-to-Have Skills\nUnderstanding of distributed training/inference and parallelism strategies - data, pipeline, tensor, and expert - and their communication patterns when scaling across multi-GPU hardware.\nUnderstanding of LLM inference and training mechanics: prefill vs. decode, KV cache, batching policies, and quantization.\nExposure to TRT-LLM, vLLM, or SGLang.\nFamiliarity with Git/GitHub, CI/CD, and automated workflows.\nUnderstanding of power fundamentals and power/performance co-optimization.\nJob Type:\nCollege GradShift:\nShift 1 (India)Primary Location:\nIndia, BangaloreAdditional 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 be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * 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. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.","description_format":"text","description_chars":3875,"description_truncated":false,"requirements":{"experience_years_min":1,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Hybrid work"],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Semiconductor Manufacturing","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-23T17:59:23Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":2,"expected_fill_days":30,"reasons":["conf:2","stale_co","velocity","win:early","comp:junior,brand"],"computed_at":"2026-10-24T06:02:35Z"},"pay":null,"html_url":"https://alion.io/job/intel-ai-system-performance-engineer","json_url":"https://alion.io/job/intel-ai-system-performance-engineer.json","meta":{"generated_at":"2026-10-24T16:43:57Z","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":24242,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-25T00:00:00Z"}},"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":35},"rest":"https://alion.io/mcp/rest/get_company?id=35"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fintel-ai-system-performance-engineer"},{"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%2Fintel-ai-system-performance-engineer"},{"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%2Fintel-ai-system-performance-engineer"},{"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/intel-ai-system-performance-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fintel-ai-system-performance-engineer"}]}