{"schemaVersion":"jobsearcher.job.v1","id":"7ecab3fc8aa9bd6fa6442721","url":"https://jobsearcher.com/jobs/7ecab3fc8aa9bd6fa6442721","canonicalUrl":"https://jobsearcher.com/jobs/7ecab3fc8aa9bd6fa6442721","title":"SRE Mlops","description":"Design and implement cloud solutions, build MLOps on cloud (AWS or GCP)Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Flux, Kustomize, Circle CI, Airflow or similar toolsData science model containerization, deployment using docker, VLLM, KubernetesData science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its qualityData science models testing, validation and tests automationCommunicate with a team of data scientists, data engineers and architects, document the processesDevelop and deploy scalable tools and services for our clients to handle machine learning training and inferenceQualifications: 6+ years of experience in ML Ops with strong knowledge in Kubernetes, 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continuous integrationExposure to machine learning methodology and best practicesGood communication skills and ability to work in a team","company":"Natsoft","rawCompany":"natsoft","city":"Austin","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-09-02T08:18:28.316Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"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":"541519","title":"Other Computer Related Services","slug":"other-computer-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"SRE Mlops","description":"Design and implement cloud solutions, build MLOps on cloud (AWS or GCP)Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Flux, Kustomize, Circle CI, Airflow or similar toolsData science model containerization, deployment using docker, VLLM, KubernetesData science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its qualityData science models testing, validation and tests automationCommunicate with a team of data scientists, data engineers and architects, document the processesDevelop and deploy scalable tools and services for our clients to handle machine learning training and inferenceQualifications: 6+ years of experience in ML Ops with strong knowledge in Kubernetes, Python, MongoDB and AWS.Good understanding of Apache SOLR.Proficient with Linux administration.Knowledge of ML models and LLM.Ability to understand tools used by data scientists and experience with software development and test automationAbility to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS or GCP)Experience working with cloud computing and database systemsExperience building custom integrations between cloud-based systems using APIsExperience developing and maintaining ML systems built with open-source toolsExperience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and KubernetesExperience developing containers and Kubernetes in cloud computing environmentsFamiliarity with one or more data-oriented workflow orchestration frameworks (Kubeflow, Airflow, Argo, etc.)Ability to translate business needs to technical requirementsStrong understanding of software testing, benchmarking, and continuous integrationExposure to machine learning methodology and best practicesGood communication skills and ability to work in a 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