{"schemaVersion":"jobsearcher.job.v1","id":"8b23b4dc330b79271c7721ce","url":"https://jobsearcher.com/jobs/8b23b4dc330b79271c7721ce","canonicalUrl":"https://jobsearcher.com/jobs/8b23b4dc330b79271c7721ce","title":"Machine Learning Systems Engineer, Networking","description":"Join our team of innovative engineers who are building an AI Data Center AIOps platform that turns raw, high-volume telemetry into reliable, job-centric insights and automation for GPU fleets. As an ML Engineer on this team, you'll design and implement ML algorithms that run in real-time streaming pipelines, detecting anomalies and surfacing insights across massive-scale infrastructure before they impact AI training and inference.\nThe core challenge of this role is building ML algorithms that are simultaneously accurate and efficient —processing millions of telemetry streams in real time within tight CPU and memory budgets. You'll need both the data science depth to design and validate algorithms and the engineering discipline to implement them in production at scale.\nWhat you'll be doing:\nImplement production ML algorithms in Go — optimized for real-time streaming pipelines operating at massive scale under strict resource constraints\nDesign and develop new ML algorithms where needed: anomaly detection, health scoring, and predictive analytics on high-volume time-series telemetry from GPU and network infrastructure\nImprove and extend existing algorithms and experiment with new approaches suited to real-time streaming constraints\nBuild and maintain end-to-end ML pipelines — from data ingestion and schema design through model inference — optimized for on-premises, latency-sensitive deployments\nPartner with the Data Science team on algorithm design, prototype evaluation, and translating research findings into platform requirements\nWhat we need to see:\nA BS (or equivalent experience) and 5+ years of experience, MS and 3+ years, or PhD with 1+ years in Computer Science, Statistics, or a related field\nStrong mathematical foundation: statistics, probability, linear algebra, and algorithm analysis\nProven experience implementing and optimizing ML algorithms in production — this is a coding-first role; strong implementation skills are required\nStrong programming skills in one or more of Go, C/C++, Rust, or Scala; Python working knowledge is a plus\nFamiliarity with time-series databases and streaming data architectures\nAbility to work independently and navigate ambiguity in a fast-paced engineering environment\nWays to stand out from the crowd:\nData Science background with hands-on experience building and validating ML models — bridging research and production implementation\nExperience implementing ML algorithms directly in systems languages for latency-sensitive or resource-constrained environments\nResearch experience: knowing the latest ML literature and translating advances into practical improvements\nExperience with Kafka-based streaming pipelines and real-time feature engineering at scale\nWith competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.\nYou will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until May 22, 2026.\nThis posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.","company":"NVIDIA","rawCompany":"nvidia","city":"Santa Clara","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-29T11:42:58.601Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Systems Engineer, Networking","description":"Join our team of innovative engineers who are building an AI Data Center AIOps platform that turns raw, high-volume telemetry into reliable, job-centric insights and automation for GPU fleets. As an ML Engineer on this team, you'll design and implement ML algorithms that run in real-time streaming pipelines, detecting anomalies and surfacing insights across massive-scale infrastructure before they impact AI training and inference.\nThe core challenge of this role is building ML algorithms that are simultaneously accurate and efficient —processing millions of telemetry streams in real time within tight CPU and memory budgets. You'll need both the data science depth to design and validate algorithms and the engineering discipline to implement them in production at scale.\nWhat you'll be doing:\nImplement production ML algorithms in Go — optimized for real-time streaming pipelines operating at massive scale under strict resource constraints\nDesign and develop new ML algorithms where needed: anomaly detection, health scoring, and predictive analytics on high-volume time-series telemetry from GPU and network infrastructure\nImprove and extend existing algorithms and experiment with new approaches suited to real-time streaming constraints\nBuild and maintain end-to-end ML pipelines — from data ingestion and schema design through model inference — optimized for on-premises, latency-sensitive deployments\nPartner with the Data Science team on algorithm design, prototype evaluation, and translating research findings into platform requirements\nWhat we need to see:\nA BS (or equivalent experience) and 5+ years of experience, MS and 3+ years, or PhD with 1+ years in Computer Science, Statistics, or a related field\nStrong mathematical foundation: statistics, probability, linear algebra, and algorithm analysis\nProven experience implementing and optimizing ML algorithms in production — this is a coding-first role; strong implementation skills are required\nStrong programming skills in one or more of Go, C/C++, Rust, or Scala; Python working knowledge is a plus\nFamiliarity with time-series databases and streaming data architectures\nAbility to work independently and navigate ambiguity in a fast-paced engineering environment\nWays to stand out from the crowd:\nData Science background with hands-on experience building and validating ML models — bridging research and production implementation\nExperience implementing ML algorithms directly in systems languages for latency-sensitive or resource-constrained environments\nResearch experience: knowing the latest ML literature and translating advances into practical improvements\nExperience with Kafka-based streaming pipelines and real-time feature engineering at scale\nWith competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.\nYou will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until May 22, 2026.\nThis posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.","datePosted":"2026-07-29T11:42:58.601Z","dateModified":"2026-07-29T11:42:58.601Z","hiringOrganization":{"@type":"Organization","name":"NVIDIA","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Santa Clara","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"8b23b4dc330b79271c7721ce"},"url":"https://jobsearcher.com/jobs/8b23b4dc330b79271c7721ce"}}