{"schemaVersion":"jobsearcher.job.v1","id":"1291c0d65897fb1c6e19d48c","url":"https://jobsearcher.com/jobs/1291c0d65897fb1c6e19d48c","canonicalUrl":"https://jobsearcher.com/jobs/1291c0d65897fb1c6e19d48c","title":"Solutions Engineer","description":"We’re looking for a Forward Deployment Engineer (FDE) to work directly with customers and partners to design, deploy, and validate Inference dedicated endpoint & Model-as-a-Service products on GMI’s global infrastructure.\n\nThis is a high-impact, hybrid engineering role that sits at the intersection of platform engineering, applied ML, and customer success. You’ll be embedded with customers during early-stage deployments—turning research ideas, datasets, and business requirements into working, performant systems on real GPU clusters.\n\nIf you enjoy being close to users, debugging real systems, and shipping results fast (not just writing docs), this role is for you.\n\nWhat You’ll Do\nOwn customer POCs end-to-end\n\nDeploy and optimize LLM and multi-modal inference workflows on GMI clusters\n\nTranslate customer requirements into concrete system designs and experiments\n\nForward-deploy with customers\n\nWork hands‑on with research teams, startups, and enterprise customers\n\nDebug performance, stability, and correctness issues in real environments\n\nStand up and tune inference stacks (e.g. vLLM / SGLang / Ray Serve–style architectures)\n\nOptimize latency, throughput, GPU utilization, and cost efficiency\n\nHelp customers test, evaluate, and adopt the most frontier LLM and multi-modal models through GMI's unified API\n\nGuide model selection, API integration, and migration across providers; shorten the \"idea → production\" cycle\n\nValidate correctness, compatibility, and performance across the MaaS model catalog\n\nPerformance & reliability\n\nDiagnose GPU, networking, and distributed system bottlenecks\n\nRun benchmarks, profiling, and stress tests on multi‑GPU / multi‑node setups\n\nFeedback loop to product\n\nFeed real-world customer learnings back into GMI’s platform, SDKs, and APIs\n\nHelp shape reference architectures, cookbooks, and best practices\n\nWhat We’re Looking For\nCore Requirements\n\nProficiency in at least one programming language (Python and Golang preferred)\n\nSolid understanding of software systems and distributed systems\n\nHands‑on experience with ML inference or serving systems\n\nComfort working directly with customers and ambiguous requirements\n\nAbility to debug end‑to‑end systems (code, infra, networking, performance)\n\nNice to Have\n\nExperience with:\n\nGlobal, distributed systems\n\nHands‑on experience developing and maintaining production services on Kubernetes\n\nGPU performance profiling, optimization, and inference benchmarking\n\nPrior experience as:\n\nSolutions Engineer\n\nApplied Research Engineer\n\nWhat Makes This Role Special\n\nYou’re close to real users and real GPUs —not abstract roadmaps\n\nYou’ll work on cutting‑edge inference and frontier models , not toy demos\n\nYou’ll influence product direction through direct customer feedback\n\nFast iteration, high ownership, and visible impact\n\nWho Thrives Here\n\nEngineers who like shipping over theorizing\n\nPeople who enjoy being the \"last mile\" problem solver\n\nBuilders who want exposure to both deep systems and applied ML\n\nThose excited by early‑stage POCs that turn into real production systems\n\n#J-18808-Ljbffr","company":"Gmi Cloud","rawCompany":"gmi cloud","city":"Mountain View","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-07-16T03:15:10.807Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"41-9031.00","title":"Sales Engineers","slug":"sales-engineers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Solutions Engineer","description":"We’re looking for a Forward Deployment Engineer (FDE) to work directly with customers and partners to design, deploy, and validate Inference dedicated endpoint & Model-as-a-Service products on GMI’s global infrastructure.\n\nThis is a high-impact, hybrid engineering role that sits at the intersection of platform engineering, applied ML, and customer success. You’ll be embedded with customers during early-stage deployments—turning research ideas, datasets, and business requirements into working, performant systems on real GPU clusters.\n\nIf you enjoy being close to users, debugging real systems, and shipping results fast (not just writing docs), this role is for you.\n\nWhat You’ll Do\nOwn customer POCs end-to-end\n\nDeploy and optimize LLM and multi-modal inference workflows on GMI clusters\n\nTranslate customer requirements into concrete system designs and experiments\n\nForward-deploy with customers\n\nWork hands‑on with research teams, startups, and enterprise customers\n\nDebug performance, stability, and correctness issues in real environments\n\nStand up and tune inference stacks (e.g. vLLM / SGLang / Ray Serve–style architectures)\n\nOptimize latency, throughput, GPU utilization, and cost efficiency\n\nHelp customers test, evaluate, and adopt the most frontier LLM and multi-modal models through GMI's unified API\n\nGuide model selection, API integration, and migration across providers; shorten the \"idea → production\" cycle\n\nValidate correctness, compatibility, and performance across the MaaS model catalog\n\nPerformance & reliability\n\nDiagnose GPU, networking, and distributed system bottlenecks\n\nRun benchmarks, profiling, and stress tests on multi‑GPU / multi‑node setups\n\nFeedback loop to product\n\nFeed real-world customer learnings back into GMI’s platform, SDKs, and APIs\n\nHelp shape reference architectures, cookbooks, and best practices\n\nWhat We’re Looking For\nCore Requirements\n\nProficiency in at least one programming language (Python and Golang preferred)\n\nSolid understanding of software systems and distributed systems\n\nHands‑on experience with ML inference or serving systems\n\nComfort working directly with customers and ambiguous requirements\n\nAbility to debug end‑to‑end systems (code, infra, networking, performance)\n\nNice to Have\n\nExperience with:\n\nGlobal, distributed systems\n\nHands‑on experience developing and maintaining production services on Kubernetes\n\nGPU performance profiling, optimization, and inference benchmarking\n\nPrior experience as:\n\nSolutions Engineer\n\nApplied Research Engineer\n\nWhat Makes This Role Special\n\nYou’re close to real users and real GPUs —not abstract roadmaps\n\nYou’ll work on cutting‑edge inference and frontier models , not toy demos\n\nYou’ll influence product direction through direct customer feedback\n\nFast iteration, high ownership, and visible impact\n\nWho Thrives Here\n\nEngineers who like shipping over theorizing\n\nPeople who enjoy being the \"last mile\" problem solver\n\nBuilders who want exposure to both deep systems and applied ML\n\nThose excited by early‑stage POCs that turn into real production systems\n\n#J-18808-Ljbffr","datePosted":"2026-07-16T03:15:10.807Z","dateModified":"2026-07-16T03:15:10.807Z","hiringOrganization":{"@type":"Organization","name":"Gmi Cloud","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1291c0d65897fb1c6e19d48c"},"url":"https://jobsearcher.com/jobs/1291c0d65897fb1c6e19d48c"}}