{"id":3426666,"url":"https://alion.io/job/qualcomm-senior-ai-performance-architect-2","title":"Senior AI Performance Architect","company":{"id":94,"name":"Qualcomm","domain":"qualcomm.com","url":"https://alion.io/company/qualcomm","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"C","score":69,"open_postings":1046,"ghost_share":0.25,"stale_share":0.149,"repost_share":0.458,"time_to_fill_p50_days":74,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Diego, United States","Austin, United States","Folsom, United States","Raleigh, United States","Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":126700,"max":190100,"currency":"USD","period":"year","gross":null,"usd_annual":190100},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Edge AI","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"C++","optional":true},{"name":"DeepSpeed","optional":true},{"name":"Fine-tuning","optional":true},{"name":"FSDP","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Rest-Assured","optional":true},{"name":"TensorFlow","optional":true},{"name":"TensorFlow C++","optional":true}],"status":"live","first_seen_at":"2026-10-28T22:41:04Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-02T11:44:08Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Company:\nQualcomm Technologies, Inc.Job Area:\nEngineering Group, Engineering Group > Machine Learning EngineeringGeneral Summary:\nToday, more intelligence is moving to end devices, and mobile is becoming a pervasive AI platform. At the same time, data centers are expanding AI capability through widespread deployment of ML accelerators. Qualcomm envisions making AI ubiquitous - expanding beyond mobile and powering other end devices, data centers, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, data center and 5G to make this a reality.\nWe are looking for AI Accelerator Architecture Engineers to drive functional, performance and power enhancements into the HW to enable state of the art training capabilities. AI inference and training systems must scale to a large number of accelerators, servers and racks. Our devices must be designed to scale to handle the largest of today's models.\nThe AI Architecture team is comprised of experts that span the full gamut from software architecture, algorithm development, kernel optimization, down to hardware accelerator block architecture and SOC design. The ideal candidate will augment the team by contributing to one or many of these areas.\nResponsibilities:\nUnderstand trends in ML network design through customer engagements and latest academic research and determine how this will affect both SW and HW design\n\nWork with customers to determine hardware requirements for AI training systems\n\nAnalysis of current accelerator and GPU architectures\n\nArchitect enhancements required for efficient training of AI models\n\nDesign and architecture of:\n\nFlexible Computational Blocks\nInvolving a variety of datatypes : floating point, fixed point, microscaling\n\nInvolving a variety of precision : 32/16/8/4/2/1\n\nCapable of optimally performing dense and sparse GEMM, GEMV\n\nMemory Technology and subystems that are optimized for a range of requirements\nCapacity\n\nBandwidth\n\nCompute in Memory, Compute near memory\n\nScale-Out and Scale-Up Architectures\nSwitches, NoCs, Codesign with Communication Collectives\n\nOptimized for Power\n\nAbility to perform Competitive Analysis\n\nCodesign HW with SW/GenAI (LLM) requirements\n\nDefine performance models to prove effectiveness of architecture proposals\n\nPre-Silicon prediction of performance for various ML training workloads\n\nPerform analysis of performance/area/power trade-offs for future HW and SW ML algorithms including impact of SOC components (memory and bus impacts)\n\nRequirements:\nMaster's degree in Computer Science, Engineering, Information Systems, or related field\n\n3+ years Hardware Engineering experience defining architecture of GPUs or accelerators used for training of AI models\n\nIn-depth knowledge of nVidia/AMD GPU capabilities and architectures\n\nKnowledge of LLM architectures and their HW requirements\n\nPreferred Skills and Experience:\nKnowledge of computer architecture, digital circuits and hardware simulators\n\nKnowledge of communication protocols used in AI systems\n\nKnowledge of Network-on-Chip (NoC) designs used in System-on-Chip (SoC) designs\n\nUnderstanding of various memory technologies used in AI systems\n\nExperience in modeling hardware and workloads in order to extract performance and power estimates\n\nHigh-level hardware modeling experience preferred\n\nKnowledge of AI Training systems such as NVIDIA DGX and NVL72\n\nExperience training and finetuning LLMs using distributed training framework such as DeepSpeed, FSDP\n\nKnowledge of front-end ML frameworks (i.e.,TensorFlow, PyTorch) used for training of ML models\n\nStrong communication skills (written and verbal)\n\nDetail-oriented with strong problem-solving, analytical and debugging skills\n\nDemonstrated ability to learn, think and adapt in a fast-changing environment\n\nAbility to code in C++ and Python\n\nKnowledge of a variety of classes of ML models (i.e. CNN, RNN, etc)\n\nMinimum Qualifications:\n• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.OR\nMaster's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.\nOR\nPhD in Computer Science, Engineering, Information Systems, or related field.\nQualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail  or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).\nTo all Staffing and Recruiting Agencies:Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.\nEEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.\nQualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.\nPay rangeand Other Compensation & Benefits :\n$126,700.00 - $190,100.00The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.\nIf you would like more information about this role, please contact Qualcomm Careers.","description_format":"text","description_chars":7234,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Autonomous Driving","RF & Wireless Hardware","Car Electronics"],"lifecycle":[{"event":"open","at":"2026-10-28T22:41:04Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 55 · green card filings: 6","filings_12m":55,"filings_prev_12m":87,"green_card_filings_12m":6,"median_offered_wage_usd":122008,"route":null,"cap_exempt":false,"checked_at":"2026-10-29T16:27:21+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":25}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":74,"reasons":["conf:3","velocity","win:early","comp:brand"],"computed_at":"2026-11-02T06:13:15Z"},"pay":{"stated_usd_annual":190100,"is_top_pay":false},"html_url":"https://alion.io/job/qualcomm-senior-ai-performance-architect-2","json_url":"https://alion.io/job/qualcomm-senior-ai-performance-architect-2.json","meta":{"generated_at":"2026-11-02T13:47:15Z","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":18776,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-03T00:00:00Z"}},"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":94},"rest":"https://alion.io/mcp/rest/get_company?id=94"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fqualcomm-senior-ai-performance-architect-2"},{"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%2Fqualcomm-senior-ai-performance-architect-2"},{"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%2Fqualcomm-senior-ai-performance-architect-2"},{"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/qualcomm-senior-ai-performance-architect-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fqualcomm-senior-ai-performance-architect-2"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3426666}},{"tool":"search_jobs","arguments":{"company":"qualcomm.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3426666},"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. 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