{"id":2644391,"url":"https://alion.io/job/google-machine-learning-hardware-architect-google-cloud-silicon","title":"Machine Learning Hardware Architect, Google Cloud Silicon","company":{"id":82,"name":"Google","domain":"google.com","url":"https://alion.io/company/google","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":101,"ghost_share":0,"stale_share":0.98,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Hardware","role_family":"Hardware","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":["Tel Aviv, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":135000,"max_usd":281000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":557},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Edge AI","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"TPU","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-15T16:08:30Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T23:12:57Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the job\nIn this role, you’ll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You’ll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.\nIn this role, you will own and lead the architecture of the Google Edge AI accelerators. You will work with the Google AI community and with external partners. You will combine the latest innovations in Machine Learning and integrated circuits to create advanced hardware acceleration solutions for Machine Learning training and inference.\nThe AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.\nWe're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.\n Responsibilities\nCreate differentiated architectural innovations for Google’s semiconductor Edge AI roadmap.\nMonitor industrial and academic trends in artificial intelligence and determine where they should intersect our roadmaps.\nEvaluate the power, performance, and cost of prospective architecture and subsystems.\nEngage with system and application software engineers to ensure optimization of the entire hardware/software stack.\nEngage with design, verification, and validation engineers to realize the architecture.\nQualifications\nMinimum qualifications:\nBachelor's degree in Electrical Engineering, Computer Engineering, or equivalent practical experience.\n10 years of experience in SoC engineering and architecture.\nExperience with performance modeling, workload analysis, and hardware-software co-design.\nPreferred qualifications:\nMaster’s degree or PhD in Electrical Engineering, Computer Engineering, or a related field.\n5 years of experience leading the architectural definition of AI accelerator architecture from concept through production.\nExperience in system-level integration and deploying complex AI models on sophisticated hardware platforms.\nExperience leading the architecture and technical direction for hardware or system-level projects.","description_format":"text","description_chars":3082,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":5,"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":["Digital Media","Marketing Analytics & Attribution","Streaming & OTT Platforms","Consumer Internet Groups"],"lifecycle":[{"event":"open","at":"2026-10-15T19:36:42Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":0,"expected_fill_days":30,"reasons":["conf:6","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-16T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/google-machine-learning-hardware-architect-google-cloud-silicon","json_url":"https://alion.io/job/google-machine-learning-hardware-architect-google-cloud-silicon.json","meta":{"generated_at":"2026-10-16T08:27:06Z","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":6364,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-17T00:00:00Z"}},"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":82},"rest":"https://alion.io/mcp/rest/get_company?id=82"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fgoogle-machine-learning-hardware-architect-google-cloud-silicon"},{"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%2Fgoogle-machine-learning-hardware-architect-google-cloud-silicon"},{"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%2Fgoogle-machine-learning-hardware-architect-google-cloud-silicon"},{"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/google-machine-learning-hardware-architect-google-cloud-silicon\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fgoogle-machine-learning-hardware-architect-google-cloud-silicon"}]}