NVIDIA
Senior Applied Research Scientist – Computational Geometry and Meshingmill
Be an Early Applicant
Develop computational geometry, mesh generation, discretization, and CAD-to-simulation algorithms for NVIDIA GPU platforms. Research differentiable and AI-native geometry processing, adaptive meshing, solver-aware methods, and simulation-ready representations. Establish benchmarks for mesh quality, robustness, accuracy, and end-to-end performance. Collaborate with research, engineering, university, and industrial teams across CAE, EDA, semiconductor, digital twin, and scientific-computing workflows.
Industrial simulation depends on turning product and device geometry into valid, efficient discretizations. This role will advance computational geometry, meshing, simulation-ready representations, and AI-native algorithms for NVIDIA GPU platforms.
We are looking for an applied researcher who can build methods that move design data reliably from CAD to simulation. You will develop geometry, meshing, and discretization algorithms that improve robustness, numerical accuracy, and end-to-end performance across CAE, EDA, semiconductor, and scientific-computing workflows. Join us in reinventing the geometric foundation of engineering simulation!
What you'll be doing:
- Build algorithms for computational geometry, computer-aided engineering and design interoperability, mesh generation, mesh adaptation, spatial data structures, and curved discretization.
- Investigate differentiable geometry, AI-native geometry processing, learning-based meshing and discretization, and design-to-simulation workflows for inverse design, simulation-ready digital twins, and autonomous engineering workflows.
- Explore solver- and hardware-aware geometry and discretization methods that jointly optimize mesh quality, numerical accuracy, robustness, and comprehensive simulation efficiency.
- Define benchmarks for mesh quality, geometry conversion, discretization accuracy, robustness, downstream solver impact, and end-to-end simulation performance.
- Collaborate with teams across Omniverse, OpenUSD, Warp, solver engineering, NVIDIA Research, universities, and industrial partners involved in computer-aided engineering, electronic design automation, chip manufacturing, electronics, and digital twin workflows.
What we need to see:
- PhD or equivalent experience in computer science, computational geometry, scientific computing, graphics, applied mathematics, computational mechanics, engineering, or a related field.
- 5+ years of experience.
- Background in computational geometry, geometry processing, mesh generation, adaptive discretization, CAD and CAE algorithms, or simulation-ready representations with 5+ years proven experience working in computational engineering.
- C++ and Python skills, with experience building algorithms for sophisticated geometry.
- Understanding of boundary representations, topology, mesh quality, discretization error, numerical robustness, and solver requirements, supported by research, software, or industrial impact.
Ways to stand out from the crowd:
- Experience with CAD kernels or formats such as Parasolid, ACIS, Open Cascade, CATIA, NX, Creo, SOLIDWORKS, STEP, IGES, B-Rep, NURBS, or spline-based representations.
- Experience with tetrahedral, hexahedral, polyhedral, anisotropic, adaptive, boundary-layer, curved, or high-order mesh generation.
- Work in isogeometric analysis, remeshing, meshless methods, topology optimization, shape optimization, differentiable geometry, or AI-native mesh generation.
- Experience with geometry repair, feature or simulation-intent recognition, parameterization, persistent correspondence, learning-based geometry representations, GPU spatial algorithms, or solver-aware adaptation.
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Own post-sale customer implementations of Samsara’s IoT technology, from solution workshops and project planning through deployment and time-to-value. Lead change management, training, demonstrations, stakeholder communication, and obstacle resolution across multiple concurrent engagements. Partner cross-functionally with Sales, Support, Sales Engineering, and Product while managing customer relationships and implementation outcomes. The role requires travel to customer sites up to 30% of the time and fluency in English and German.
Top Skills:
AIAutomationHardwareInternet Of Things (Iot)SaaS
Artificial Intelligence • Consumer Web • Digital Media • Information Technology • Social Impact • Software
Build and own evaluation infrastructure, observability tooling, datasets, annotation workflows, and diagnostic systems for production AI agents. Lead experiments across prompts, models, routing, caching, cost, and latency. Diagnose failures across planning, tool use, and agent execution, while partnering with AI Core engineering. Manage and grow the AI Quality team as a hands-on player-coach, contributing directly to production code and technical direction.
Top Skills:
Ai AgentsAnnotation WorkflowsBraintrustCachingCi/CdEvaluation FrameworksLangsmithLlmsModel RoutingObservability ToolingPythonRuby On Rails
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Manage and grow a dispersed sales engineering team supporting enterprise customers across Germany, France, and broader Mainland Europe. Partner with account executives and regional sales leaders on account planning, sales strategy, and customer calls. Oversee team performance, pre-sales escalations, and cross-functional collaboration with product, marketing, support, and customer success. Act as a trusted technical advisor and improve sales engineering practices across the organization.
Top Skills:
Cloud TechnologiesInfrastructureIotNetworkingPhysical SecuritySaaSSecurity
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories


