{"id":2736161,"url":"https://alion.io/job/nvidia-implementation-methodology-engineer-gpu","title":"Implementation Methodology Engineer - GPU","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":592,"ghost_share":0.019,"stale_share":0.66,"repost_share":0.034,"time_to_fill_p50_days":33,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":136000,"max":218500,"currency":"USD","period":"year","gross":null,"usd_annual":218500},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false},{"name":"HPC","optional":true}],"status":"live","first_seen_at":"2026-05-19T00:00:00Z","employer_posted_date":"2026-05-19","last_verified_at":"2026-10-17T04:27:35Z","board_verified":true,"closed_at":null,"days_open":151,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":151},"description":"We are looking for an Implementation Methodology Engineer to join NVIDIA VLSI team. If you are looking for a challenging and exciting role and you are a self-starter and highly motivated individual who loves to collaborate and find solutions to hard technical problems, join us today!\nNVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to pursue, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today.\nWhat you’ll be doing:\nYou will be responsible for all aspects of front-end design implementation methodologies (synthesis, formal-equivalence-checking), flow automation and application support.\n\nUse NVIDIA implementation flows and EDA tool expertise to improve power, performance and area on NVIDIA's most critical designs\n\nYou will collaborate with logic designers, physical designers and EDA vendors to solve exciting implementation issues and develop new solutions.\n\nProvide support for EDA tools and flows\n\nWhat we need to see:\nBS or MS in Electrical Engineering, Computer Engineering, or related fields (or equivalent experience).\n\n4+ years of experience in logic design implementation and/or physical design implementation\n\nDeep understanding of logic optimization techniques and relative area, timing, and power trade-offs\n\nStrong understanding of physical design implementation eg: physical synthesis, placement, routing, logic restructuring, etc.\n\nShould be a power user of synthesis and/or place and route EDA tools from Synopsys (DC/FC), Cadence (Genus/Innovus)\n\nGood debugging and problem-solving skills\n\nStrong interpersonal skills along with the ability to work in a dynamic team\n\nWays to stand out from the crowd :\nPrior experience in physical implementation\n\nProficiency in Python, Tcl, Make scripting\n\nNVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and dedicated people in the world working for us. Are you creative and autonomous? Do you love the challenge of constant innovation and creating the highest performance products in the industry? If so, we want to hear from you. Come, join NVIDIA VLSI team and help build the real-time, cost-effective computing platform driving our success across multiple fields such as Deep Learning and AI, Robotics and Autonomous Driving, Gaming and High Performance Computing.\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until May 23, 2026.This posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.","description_format":"text","description_chars":3647,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Servers & Data Center Hardware","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-16T19:06:27Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.217,"p_room":0.28,"age_days":151,"expected_fill_days":33,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":218500,"is_top_pay":true},"html_url":"https://alion.io/job/nvidia-implementation-methodology-engineer-gpu","json_url":"https://alion.io/job/nvidia-implementation-methodology-engineer-gpu.json","meta":{"generated_at":"2026-10-17T06:38:30Z","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":8998,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"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":6},"rest":"https://alion.io/mcp/rest/get_company?id=6"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnvidia-implementation-methodology-engineer-gpu"},{"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%2Fnvidia-implementation-methodology-engineer-gpu"},{"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%2Fnvidia-implementation-methodology-engineer-gpu"},{"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/nvidia-implementation-methodology-engineer-gpu\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnvidia-implementation-methodology-engineer-gpu"}]}