{"schemaVersion":"jobsearcher.job.v1","id":"14f61ba083b3345d6cafa758","url":"https://jobsearcher.com/jobs/14f61ba083b3345d6cafa758","canonicalUrl":"https://jobsearcher.com/jobs/14f61ba083b3345d6cafa758","title":"Machine Learning Engineer","description":"Machine Learning Engineer\nWashington, DC (Hybrid)\n\nAbout the Role:\n\nWe are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You’ll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.\n\nKey Responsibilities:\nDesign, implement, and maintain ML deployment pipelines for scalable production systems.\nOperationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.\nBuild robust model monitoring, logging, and alerting systems to track performance and detect drift.\nPartner with data scientists to transition models from research/prototype into production-ready deployments.\nDevelop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.\nOptimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.\nApply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.\nCollaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.\nQualifications:\n5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.\nProven experience deploying and maintaining machine learning models in production at scale.\nHands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).\nStrong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.\nDeep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.\nExpertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.\nStrong understanding of MLOps best practices, monitoring, and automation.\nExcellent problem-solving skills, with an emphasis on building reliable, scalable systems.\nStrong communication and collaboration skills across technical and non-technical teams.","company":"Ai Squared","rawCompany":"ai squared","city":"Washington","state":"DC","isRemote":false,"isActive":false,"createdAt":"2026-05-15T05:28:11.920Z","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":"15-2051.00","title":"Data Scientists","slug":"data-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":"Machine Learning Engineer","description":"Machine Learning Engineer\nWashington, DC (Hybrid)\n\nAbout the Role:\n\nWe are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You’ll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.\n\nKey Responsibilities:\nDesign, implement, and maintain ML deployment pipelines for scalable production systems.\nOperationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.\nBuild robust model monitoring, logging, and alerting systems to track performance and detect drift.\nPartner with data scientists to transition models from research/prototype into production-ready deployments.\nDevelop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.\nOptimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.\nApply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.\nCollaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.\nQualifications:\n5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.\nProven experience deploying and maintaining machine learning models in production at scale.\nHands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).\nStrong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.\nDeep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.\nExpertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.\nStrong understanding of MLOps best practices, monitoring, and automation.\nExcellent problem-solving skills, with an emphasis on building reliable, scalable systems.\nStrong communication and collaboration skills across technical and non-technical teams.","datePosted":"2026-05-15T05:28:11.920Z","dateModified":"2026-05-15T05:28:11.920Z","hiringOrganization":{"@type":"Organization","name":"Ai Squared","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Washington","addressRegion":"DC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"14f61ba083b3345d6cafa758"},"url":"https://jobsearcher.com/jobs/14f61ba083b3345d6cafa758"}}