{"id":708356,"url":"https://alion.io/job/vinci4d-physics-applications-researcher","title":"Physics Applications - Researcher","company":{"id":716702,"name":"Getvinci","domain":"getvinci.ai","url":"https://alion.io/company/getvinci","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":8,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-21T05:46:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":190000,"max":260000,"currency":"USD","period":"year","gross":null,"usd_annual":260000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"Embeddings","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"PyTorch","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-06-10T18:13:58Z","employer_posted_date":"2026-06-10","last_verified_at":"2026-10-21T22:37:34Z","board_verified":true,"closed_at":null,"days_open":133,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":132},"description":"The Mission\nAt Vinci, we are building the operator intelligence infrastructure that modern hardware programs rely on daily. We have already proven that a single foundation model works out of the box across physics on realistic production workloads.\nTrained on PetaBytes of structured physics data\n\nRunning billion-voxel inference in production\n\nTier-1 semiconductor and hardware customers\n\nOperating across multiple physical scales and operator regimes\n\nWe are scaling deployment at industrial magnitude:\nIncrease simulation throughput by two orders of magnitude\n\nExpand simulation capabilities to maximize utility and domain coverage\n\nSupport global, multi-entity deployment across Tier-1 ecosystems\n\nOur ambition is to become the default operator intelligence layer that hardware companies run on\n\nSolving Across Space and Time\nOur proven unified model architecture allows users to rapidly obtain steady state solutions of various partial differential equations. We are expanding this capability into the transient domain, modeling interactions, deformation and dynamics. These are promising applications where Vinci’s approach can not only reduce the compute load but also achieve greater accuracy.\nWhat You Will Do\nYour north star will be production and delivering value to our customers.\nIn this role you will leverage the Vinci framework to work on a variety of novel applications. Experiment with temporal propagation schemas, both in the classical and learned sense. You will use pre-existing data generation infrastructure to generate and curate training and verification samples. You will take modest iterative steps to prove out new utility and iterate hand in hand with customers to harden features.\nYou will work with Physicists, AI researchers, Software Engineers and Computational Geometry experts. You will work with a team to carry early prototypes through iteration and hardening all the way to customer use.\nWhat We’re Looking For\nQualifications;\nHave published work leveraging or building a simulation practice.\nMS/MSc with 4+ years experience or\n\nPhD with 2+ years experience\n\n2+ years using or building physics simulators\nFEM, FEA, Molecular Dynamics, FDTD\n\nApplied machine learning approaches\nComputer Vision, GraphNN, Transformer Architectures\n\nWorking knowledge of modern ML basics\nback prop, loss functions, generators, embeddings, transformer models\n\nExperience with some modern ML practices\nPyTorch, Numpy, Cuda\n\nTraining & Evaluation practices\n\nHave contributed to a production data processing system.\n\nWe are very excited to talk with you if you have\nApplied ML to the problem of\n\nMeshing geometry\n\nAccelerating FEM or DFT simulations\n\nExperience going from early stage prototype moving to a production environment at a Startup or National Lab\n\nHave leveraged simulation for design or data generation purposes.\n\nEngineering Expectations\nSoftware engineering fundamentals\nComfortable meeting software design standards to get code into a production environment.\n\nCapable of leveraging pre-existing infrastructure and “closing the gap” on occasion\n\nStrong CI, regression testing, and validation discipline\n\nComfort evolving core model infrastructure\n\nWhy Vinci\nJoin a rare early-stage startup that has successfully moved a foundational product from research to real-world, production environments, already serving Tier-1 semiconductor and hardware customers.\nOur Mission & Impact\nVinci is building the operator intelligence infrastructure that modern hardware programs rely on daily. We are scaling our solution to accelerate design validation from hours to seconds. You will contribute to expanding our unified model architecture, which currently runs billion-voxel inference, into the transient domain-a key frontier in modeling interactions, deformation, and dynamics. Our ambition is to become the default operator intelligence layer for hardware companies.\nGrowth & Opportunity\nThis is a unique opportunity for technical and professional growth, as you will define a foundational abstraction layer early in the company's trajectory. The team is small, friendly, and accessible. You will be empowered to \"own and architect large pieces of the system\" alongside a team of Physicists, AI researchers, Software Engineers, and Computational Geometry experts. This includes greenfield opportunities to expand Vinci’s core capabilities.\nLeadership\nYou will work with spectacular technical leaders like CTO Sarah Osentoski and CEO Hardik Kabaria, whose vision is to greatly accelerate physics simulations with ML while retaining solver grade accuracy.","description_format":"text","description_chars":4575,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","E-learning","Foundation Models"],"lifecycle":[{"event":"open","at":"2026-09-11T04:11:42Z"},{"event":"close","at":"2026-09-25T14:29:32Z"},{"event":"restore","at":"2026-09-25T14:40:11Z"}],"visa":[],"liveness":{"score":10,"band":"cold","label":"Long shot","p_open":1,"p_active":0.341,"p_room":0.28,"age_days":132,"expected_fill_days":30,"reasons":["conf:1","win:tail","crowd:"],"computed_at":"2026-10-21T05:46:15Z"},"pay":{"stated_usd_annual":260000,"is_top_pay":true},"html_url":"https://alion.io/job/vinci4d-physics-applications-researcher","json_url":"https://alion.io/job/vinci4d-physics-applications-researcher.json","meta":{"generated_at":"2026-10-21T22:52:08Z","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":32581,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-22T00:00:00Z"}},"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":716702},"rest":"https://alion.io/mcp/rest/get_company?id=716702"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvinci4d-physics-applications-researcher"},{"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%2Fvinci4d-physics-applications-researcher"},{"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%2Fvinci4d-physics-applications-researcher"},{"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/vinci4d-physics-applications-researcher\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvinci4d-physics-applications-researcher"}]}