EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.Our team is seeking a skilled and committed Senior Systems Engineer who brings deep expertise in Data DevOps/MLOps to strengthen our organization.The successful applicant will demonstrate a thorough understanding of data engineering practices, automated data pipelines, and the operational deployment of machine learning models. This position requires a collaborative individual capable of architecting, implementing, and overseeing large-scale data and ML pipelines that support our company's goals.ResponsibilitiesBuild, launch, and oversee CI/CD pipelines supporting data integration and ML model rolloutEstablish and maintain cloud-based infrastructure for data processing and model training operationsStreamline data validation, transformation, and workflow orchestration through automationPartner with data scientists, software engineers, and product teams to ensure seamless ML model integration into production environmentsImprove model serving and monitoring capabilities to increase performance and reliabilityOversee data versioning, lineage tracking, and ensure ML experiments remain reproducibleContinuously identify opportunities to improve deployment workflows, scalability, and infrastructure durabilityEnforce robust security measures that protect data integrity and meet regulatory standardsDiagnose and resolve problems across the entire data and ML pipeline lifecycleRequirementsBachelor's or Master's degree in Computer Science, Data Engineering, or related disciplineMinimum 5 years of relevant experience in Data DevOps, MLOps, or comparable positionsSkilled in cloud platforms such as Azure, AWS, or GCPExperience working with Infrastructure as Code tools like Terraform, CloudFormation, or AnsibleStrong command of containerization and orchestration tools such as Docker and KubernetesPractical experience using data processing frameworks like Apache Spark and DatabricksProgramming skills in Python, along with familiarity with data manipulation and ML libraries such as Pandas, TensorFlow, and PyTorchKnowledge of CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub ActionsHands-on experience with version control systems and MLOps platforms including Git, MLflow, and KubeflowSolid grasp of monitoring, logging, and alerting tools such as Prometheus and GrafanaStrong analytical and problem-solving capabilities, with the ability to perform well both independently and collaborativelyEffective communication and documentation skillsNice to haveExperience with DataOps principles and tools such as Airflow and dbtUnderstanding of data governance platforms like CollibraExposure to Big Data technologies such as Hadoop and HiveCloud platform or data engineering certificationsWe offerOpportunity to work on technical challenges that may impact across geographiesVast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certificationsOpportunity to share your ideas on international platformsSponsored Tech Talks & HackathonsUnlimited access to LinkedIn learning solutionsPossibility to relocate to any EPAM office for short and long-term projectsFocused individual developmentBenefit package:Health benefitsRetirement benefitsPaid time offFlexible benefitsForums to explore beyond work passion (CSR, photography, painting, sports, etc.)