{"schemaVersion":"jobsearcher.job.v1","id":"97ed8463fd502cd91a8618c8","url":"https://jobsearcher.com/jobs/97ed8463fd502cd91a8618c8","canonicalUrl":"https://jobsearcher.com/jobs/97ed8463fd502cd91a8618c8","title":"Senior Machine Learning Engineer","description":"Senior Machine Learning Engineer / AI Engineer\r\nRole Overview\r\nWe are seeking an experienced Machine Learning Engineer to design, build, and deploy scalable AI systems powering intelligent products and internal platforms. This role combines applied ML, software engineering, and production infrastructure to deliver models into real-world environments.\r\nThe ideal candidate has hands-on experience with deep learning, LLMs, data pipelines, and cloud deployment, and is comfortable working in a fast-paced engineering organization.\r\nKey Responsibilities\r\nBuild and productionize machine learning models for recommendation, prediction, classification, ranking, or generative AI use cases\r\nDevelop and fine-tune large language models, retrieval systems, and agent workflows\r\nDesign scalable ML pipelines for training, evaluation, monitoring, and inference\r\nCollaborate with product, data, and engineering teams to define AI roadmaps\r\nImprove model performance, latency, reliability, and cost efficiency\r\nImplement MLOps best practices including CI/CD, experiment tracking, and model versioning\r\nConduct A/B testing and model performance analysis in production\r\nStay current on latest research and integrate relevant advances into product systems\r\nRequired Qualifications\r\nBS/MS/PhD in Computer Science, Machine Learning, Statistics, Mathematics, or related field\r\n5+ years of software engineering or ML engineering experience\r\nStrong Python proficiency\r\nExperience with:\r\nPyTorch or TensorFlow\r\nScikit-learn\r\nSQL and distributed data systems\r\nCloud platforms: Amazon Web Services, Google Cloud, or Microsoft Azure\r\nContainerization/orchestration: Docker, Kubernetes\r\nExperience deploying APIs and backend ML services\r\nSolid understanding of:\r\nDeep learning\r\nNLP / LLM architectures\r\nFeature engineering\r\nModel evaluation and monitoring\r\nPreferred Qualifications\r\nExperience with generative AI products and LLM application development\r\nFamiliarity with:\r\nRAG systems\r\nVector databases\r\nRLHF / fine-tuning workflows\r\nModel serving at scale\r\nStartup or high-growth company experience\r\nOpen-source contributions or published ML research\r\nNice-to-Have Tools\r\nLangChain / LlamaIndex\r\nAirflow / Dagster\r\nMLflow / Weights & Biases\r\nSpark / Ray\r\nDatabricks\r\nSnowflake\r\nBenefits\r\nFull health, dental, vision\r\n401(k) matching\r\nEquity participation\r\nFlexible PTO\r\nLearning & conference budget\r\nCommuter benefits\r\nCatered meals / office stipend\r\nCompensation\r\nBase Salary:$180,000 – $260,000\r\nEquity: Competitive startup/public company equity package\r\nBonus: Performance-based annual bonus (10–20%)","company":"Disruptive Datatech","rawCompany":"disruptive datatech","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-05-10T01:30:49.569Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"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":"Senior Machine Learning Engineer","description":"Senior Machine Learning Engineer / AI Engineer\r\nRole Overview\r\nWe are seeking an experienced Machine Learning Engineer to design, build, and deploy scalable AI systems powering intelligent products and internal platforms. This role combines applied ML, software engineering, and production infrastructure to deliver models into real-world environments.\r\nThe ideal candidate has hands-on experience with deep learning, LLMs, data pipelines, and cloud deployment, and is comfortable working in a fast-paced engineering organization.\r\nKey Responsibilities\r\nBuild and productionize machine learning models for recommendation, prediction, classification, ranking, or generative AI use cases\r\nDevelop and fine-tune large language models, retrieval systems, and agent workflows\r\nDesign scalable ML pipelines for training, evaluation, monitoring, and inference\r\nCollaborate with product, data, and engineering teams to define AI roadmaps\r\nImprove model performance, latency, reliability, and cost efficiency\r\nImplement MLOps best practices including CI/CD, experiment tracking, and model versioning\r\nConduct A/B testing and model performance analysis in production\r\nStay current on latest research and integrate relevant advances into product systems\r\nRequired Qualifications\r\nBS/MS/PhD in Computer Science, Machine Learning, Statistics, Mathematics, or related field\r\n5+ years of software engineering or ML engineering experience\r\nStrong Python proficiency\r\nExperience with:\r\nPyTorch or TensorFlow\r\nScikit-learn\r\nSQL and distributed data systems\r\nCloud platforms: Amazon Web Services, Google Cloud, or Microsoft Azure\r\nContainerization/orchestration: Docker, Kubernetes\r\nExperience deploying APIs and backend ML services\r\nSolid understanding of:\r\nDeep learning\r\nNLP / LLM architectures\r\nFeature engineering\r\nModel evaluation and monitoring\r\nPreferred Qualifications\r\nExperience with generative AI products and LLM application development\r\nFamiliarity with:\r\nRAG systems\r\nVector databases\r\nRLHF / fine-tuning workflows\r\nModel serving at scale\r\nStartup or high-growth company experience\r\nOpen-source contributions or published ML research\r\nNice-to-Have Tools\r\nLangChain / LlamaIndex\r\nAirflow / Dagster\r\nMLflow / Weights & Biases\r\nSpark / Ray\r\nDatabricks\r\nSnowflake\r\nBenefits\r\nFull health, dental, vision\r\n401(k) matching\r\nEquity participation\r\nFlexible PTO\r\nLearning & conference budget\r\nCommuter benefits\r\nCatered meals / office stipend\r\nCompensation\r\nBase Salary:$180,000 – $260,000\r\nEquity: Competitive startup/public company equity package\r\nBonus: Performance-based annual bonus (10–20%)","datePosted":"2026-05-10T01:30:49.569Z","dateModified":"2026-05-10T01:30:49.569Z","hiringOrganization":{"@type":"Organization","name":"Disruptive Datatech","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"97ed8463fd502cd91a8618c8"},"url":"https://jobsearcher.com/jobs/97ed8463fd502cd91a8618c8"}}