MLOps Engineer

Job Summary - For this role, we are looking for ML Ops Engineer with Kubernetes and Python. Experience Required: 6 Plus years of experience in ML Ops with strong knowledge in Kubernetes, Python, MongoDB and AWS Technical skills: Python, Kubernetes, Mongo DB, Microservices, AWS SOLR ML operations, CI CD pipelines, LLM 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 automation Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP) Qualifications: Experience working with cloud computing and database systems Experience building custom integrations between cloud-based systems using APIs Experience developing and maintaining ML systems built with open-source tools Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes Experience developing containers and Kubernetes in cloud computing environments Familiarity with one or more data-oriented workflow orchestration frameworks (Kubeflow, Airflow, Argo, etc.) Ability to translate business needs to technical requirements Strong understanding of software testing, benchmarking, and continuous integration Exposure to machine learning methodology and best practices Good communication skills and ability to work in a team Behavioral Skills: Excellent Communication skills and collaboration skills Ability to propose and implement improvements in the system Ability to work with cross-functional stakeholders

Created: 2026-03-10