Developer Technology Engineer, Energy

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA ’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! NVIDIA islookingforapassionate, world-class computer scientists and engineers (ComputeDeveloperTechnology - DevTech)toaccelerateEnergysimulationandAIworkflowson NVIDIA platforms.YouwillfocusonCUDAperformanceoptimizationforworkloadssuchasseismicprocessing(e.g.,imaging/inversionpipelines),reservoirsimulation,powergridsimulators,andrelatedHPC/AIproductionworkflows.Youwillworkhands-onwithcustomerandpartnerengineeringteamsaswellas NVIDIA productandengineeringgroupstodelivermeasurablespeedupsandscalableperformanceonmulti-GPUandmulti-nodesystems. What you will be doing: Profile,analyze,andoptimizeGPU-acceleratedapplicationswithemphasisonCUDAkernels,memorymovement,concurrency,andend-to-endthroughput. Driveperformanceimprovementsacrossthestack: CUDAC++kerneloptimization,launchconfiguration,memoryhierarchy,streams/events GPUlibraries(asapplicable):cuBLAS,cuFFT,cuSPARSE,cuSOLVER,NCCL Multi-GPUandmulti-nodescalingusingMPI+NCCL,CPU/GPUoverlap,communicationpatterns Buildreproduciblebenchmarks,performancereports,andtuningrecommendations(before/after,methodology,scalingcurves). Developandmaintainreferenceimplementations,examples,and/orpatchestocustomercodetoenableperformanceandportability. Supportcustomerengagements(POCstoproduction),includingdebuggingcorrectness/performanceissuesandadvisingonbestpracticesfordeployment(containers,schedulers,clusters). Collaboratewithinternalteamstofileactionableissues,validatefixes,andinfluenceroadmapbasedonrealcustomerrequirementsinEnergy. Build internal libraries and resusable code that would lead to future NVIDIA products. What we needto see: BS/MS(orequivalentexperience)inCS/CE/EE/Physics/AppliedMathorrelatedfield. StrongprogrammingskillsinC/C++andPythononLinux. Hands-onexperiencewithCUDAprogrammingandGPUperformanceoptimizationconcepts. Experienceprofilinganddebuggingperformanceusingtoolssuchas NVIDIA NsightSystems/NsightCompute(orequivalent). Understandingofparallelcomputingandperformancefundamentals(vectorization,threading,NUMA,memorybandwidth/latency). Abilitytocommunicatetechnicalfindingsclearlytobothengineersandnon-engineers. 5+yearsrelevant experienceinGPU/HPCoptimization;strongtrackrecordofdeliveredspeedupsandscalingimprovements. Ways to stand out from the crowd : Leadsperformancereviewswithcustomerstakeholders;createsreusableplaybooks/referencedesigns.Experience/Skills(typical) HPCexperiencewithMPI,distributedsystems,andmulti-nodeperformancetuning. Energy/HPCdomainexposure: Seismicprocessingpipelines,RTM/FWI-stylepatterns,FFT/stencil/linearalgebraheavycodes Reservoirsimulation(sparse/iterativesolvers),preconditioning,domaindecomposition Powergridsimulation/transientstability/optimizationworkflows ExperiencewithCI/perfregressiontesting,containerizedworkflows(Docker/Apptainer),andschedulers(Slurm). FamiliaritywithAIworkflowsusedalongsidesimulation(dataprep,training/inferenceintegration,pipelineperformance). NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Originally posted on Himalayas