{"schemaVersion":"jobsearcher.job.v1","id":"fc9df0c8812b00558eeb231a","url":"https://jobsearcher.com/jobs/fc9df0c8812b00558eeb231a","canonicalUrl":"https://jobsearcher.com/jobs/fc9df0c8812b00558eeb231a","title":"AI Inference Infrastructure Software Engineer (Kubernetes / Cloud)","description":"Location: Seattle, WA (Hybrid - 3 days/week in office)\nAbout ElastixAI:\nElastixAI is an early-stage Software startup on a mission to reinvent AI inference infrastructure from the ground up. We're building a next-generation inference platform that delivers unprecedented efficiency by tightly integrating machine learning, software stack, and custom hardware. Our philosophy is simple: the best performance comes from holistic co-design, where every layer, from model architecture to kernels to silicon, works in harmony.\nIf you're excited about pushing AI performance to physical limits and shaping the future of large-scale inference, we'd love to meet you.\nRole Summary:\nWe're looking for an Inference Infrastructure Software Engineer to own and evolve the cloud and Kubernetes backbone behind our Token-as-a-Service platform. You'll be the connective tissue between our inference engine and the production environments where customers actually consume tokens — making sure our accelerated workloads run reliably, scale predictably, and deploy seamlessly across managed and self-hosted clusters.\nThis is a hands-on role with broad surface area. You'll touch everything from cluster bring-up, automating the software releases, and AI Accelerator scheduling to service reliability and cost optimization, working closely with our ML, runtime, and hardware teams to expose the full performance of our co-designed stack to end users.\nKey Responsibilities:\nBuild, operate, and evolve ElastixAI's Kubernetes infrastructure powering our Token-as-a-Service capability.\nRun accelerated inference workloads in production at scale, with strong SLAs around latency, throughput, and availability.\nManage and harden our AWS, GCP, and on-prem infrastructure, including networking, storage, IAM, and observability layers tied to our services.\nDevelop tooling and automation in Python, Bash, Rust, and Go to streamline deployments, rollouts, autoscaling, and incident response.\nPartner with the ML and runtime teams to productionize new inference capabilities, model deployments, and routing strategies.\nContribute to capacity planning, cost optimization, and reliability engineering across multi-cloud and self-hosted environments.\nHelp define the platform roadmap as we scale from early customers to broad production deployments.\nBe a member of the Elastix On-Call rotation\nRequired Qualifications:\nMinimum BS in Computer Science, Software Engineering, or a related field.\n3–5 years of hands-on Kubernetes experience, including EKS, GKE, and/or self-hosted clusters.\n2–3 years of production experience operating workloads on AWS or GCP.\nProven track record running ML or inference services at scale on Kubernetes in production.\nStrong experience running accelerated workloads in Kubernetes, scheduling, drivers, device plugins, MIG, networking, and storage considerations.\nSolid coding skills in Python, Bash and proficiency in Go\nProficient in configuring and leveraging Linux OS in production\nExperience with infrastructure-as-code (Terraform, Pulumi), OS configuration state (Ansible, Puppet, Salt) and GitOps workflows (Argo CD, Flux).\nExperience in OS configuration tooling.\nFamiliarity with AI inference and/or training workflows and the operational patterns around them.\nPragmatic, ownership-oriented mindset; comfortable operating in early-stage ambiguity and shipping iteratively.\nPreferred/Bonus Qualifications:\nMS/PhD in Computer Science, Software Engineering, or a related field.\nExperience with inference servers and runtimes (e.g., Triton, vLLM, TGI) and model-serving patterns (batching, streaming, KV-cache aware routing).\nExposure to heterogeneous accelerators beyond GPUs (FPGAs, custom ASICs).\nBackground in observability, SRE, or performance engineering for latency-sensitive services.\nExperience building customer facing API platforms including onboarding, API keys/auth management, and usage metering.\nWhat We Offer:\nA chance to be a foundational engineer in an innovative AI startup.\nA dynamic and collaborative work environment and the change to have a significant impact on new technology\nThe opportunity to work on challenging problems at the intersection of ML, software, and systems.\nCompetitive compensation and startup equity package\nComprehensive medical, dental, and vision coverage (premiums 100% paid by employer)\nFlexible Time Off (FTO)\nPaid parental leave\nGym or fitness benefit\nCommuter benefit\nInvestment in employee learning & development","company":"Elastixai","rawCompany":"elastixai","city":"Seattle","state":"WA","isRemote":false,"isActive":false,"createdAt":"2026-06-25T01:21:47.305Z","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":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"AI Inference Infrastructure Software Engineer (Kubernetes / Cloud)","description":"Location: Seattle, WA (Hybrid - 3 days/week in office)\nAbout ElastixAI:\nElastixAI is an early-stage Software startup on a mission to reinvent AI inference infrastructure from the ground up. We're building a next-generation inference platform that delivers unprecedented efficiency by tightly integrating machine learning, software stack, and custom hardware. Our philosophy is simple: the best performance comes from holistic co-design, where every layer, from model architecture to kernels to silicon, works in harmony.\nIf you're excited about pushing AI performance to physical limits and shaping the future of large-scale inference, we'd love to meet you.\nRole Summary:\nWe're looking for an Inference Infrastructure Software Engineer to own and evolve the cloud and Kubernetes backbone behind our Token-as-a-Service platform. You'll be the connective tissue between our inference engine and the production environments where customers actually consume tokens — making sure our accelerated workloads run reliably, scale predictably, and deploy seamlessly across managed and self-hosted clusters.\nThis is a hands-on role with broad surface area. You'll touch everything from cluster bring-up, automating the software releases, and AI Accelerator scheduling to service reliability and cost optimization, working closely with our ML, runtime, and hardware teams to expose the full performance of our co-designed stack to end users.\nKey Responsibilities:\nBuild, operate, and evolve ElastixAI's Kubernetes infrastructure powering our Token-as-a-Service capability.\nRun accelerated inference workloads in production at scale, with strong SLAs around latency, throughput, and availability.\nManage and harden our AWS, GCP, and on-prem infrastructure, including networking, storage, IAM, and observability layers tied to our services.\nDevelop tooling and automation in Python, Bash, Rust, and Go to streamline deployments, rollouts, autoscaling, and incident response.\nPartner with the ML and runtime teams to productionize new inference capabilities, model deployments, and routing strategies.\nContribute to capacity planning, cost optimization, and reliability engineering across multi-cloud and self-hosted environments.\nHelp define the platform roadmap as we scale from early customers to broad production deployments.\nBe a member of the Elastix On-Call rotation\nRequired Qualifications:\nMinimum BS in Computer Science, Software Engineering, or a related field.\n3–5 years of hands-on Kubernetes experience, including EKS, GKE, and/or self-hosted clusters.\n2–3 years of production experience operating workloads on AWS or GCP.\nProven track record running ML or inference services at scale on Kubernetes in production.\nStrong experience running accelerated workloads in Kubernetes, scheduling, drivers, device plugins, MIG, networking, and storage considerations.\nSolid coding skills in Python, Bash and proficiency in Go\nProficient in configuring and leveraging Linux OS in production\nExperience with infrastructure-as-code (Terraform, Pulumi), OS configuration state (Ansible, Puppet, Salt) and GitOps workflows (Argo CD, Flux).\nExperience in OS configuration tooling.\nFamiliarity with AI inference and/or training workflows and the operational patterns around them.\nPragmatic, ownership-oriented mindset; comfortable operating in early-stage ambiguity and shipping iteratively.\nPreferred/Bonus Qualifications:\nMS/PhD in Computer Science, Software Engineering, or a related field.\nExperience with inference servers and runtimes (e.g., Triton, vLLM, TGI) and model-serving patterns (batching, streaming, KV-cache aware routing).\nExposure to heterogeneous accelerators beyond GPUs (FPGAs, custom ASICs).\nBackground in observability, SRE, or performance engineering for latency-sensitive services.\nExperience building customer facing API platforms including onboarding, API keys/auth management, and usage metering.\nWhat We Offer:\nA chance to be a foundational engineer in an innovative AI startup.\nA dynamic and collaborative work environment and the change to have a significant impact on new technology\nThe opportunity to work on challenging problems at the intersection of ML, software, and systems.\nCompetitive compensation and startup equity package\nComprehensive medical, dental, and vision coverage (premiums 100% paid by employer)\nFlexible Time Off (FTO)\nPaid parental leave\nGym or fitness benefit\nCommuter benefit\nInvestment in employee learning & development","datePosted":"2026-06-25T01:21:47.305Z","dateModified":"2026-06-25T01:21:47.305Z","hiringOrganization":{"@type":"Organization","name":"Elastixai","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle","addressRegion":"WA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"fc9df0c8812b00558eeb231a"},"url":"https://jobsearcher.com/jobs/fc9df0c8812b00558eeb231a"}}