Senior Data DevOps - MLOps Expertise

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.
We are looking for a dedicated and proficient Senior Data DevOps Engineer with extensive MLOps knowledge to enhance our team.
The ideal candidate should possess a comprehensive knowledge of data engineering, data pipeline automation, and machine learning model operationalization. The role demands a cooperative professional skilled in designing, deploying, and managing extensive data and ML pipelines in alignment with organizational objectives.

• Develop, deploy, and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for data integration and machine learning model deployment
• Set up and sustain infrastructure for data processing and model training through cloud-based resources and services
• Automate processes for data validation, transformation, and workflow orchestration
• Work closely with data scientists, software engineers, and product teams for a smooth integration of ML models into production
• Enhance model serving and monitoring to boost performance and dependability
• Manage data versioning, lineage tracking, and the reproducibility of ML experiments
• Actively search for enhancements in deployment processes, scalability, and infrastructure resilience
• Implement stringent security protocols to safeguard data integrity and compliance with regulations
• Troubleshoot and solve issues throughout the data and ML pipeline lifecycle

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
• 4+ years of experience in Data DevOps, MLOps, or similar roles
• Proficiency in cloud platforms such as Azure, AWS, or GCP
• Background in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible
• Expertise in containerization and orchestration technologies including Docker and Kubernetes
• Hands-on experience with data processing frameworks such as Apache Spark and Databricks
• Proficiency in programming languages including Python with an understanding of data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
• Familiarity with CI/CD tools including Jenkins, GitLab CI/CD, and GitHub Actions
• Experience with version control tools and MLOps platforms such as Git, MLflow, and Kubeflow
• Strong understanding of monitoring, logging, and alerting systems including Prometheus and Grafana
• Excellent problem-solving abilities with capability to work independently and in teams
• Strong skills in communication and documentation

• Background in DataOps concepts and tools such as Airflow and dbt
• Knowledge of data governance platforms like Collibra
• Familiarity with Big Data technologies including Hadoop and Hive
• Certifications in cloud platforms or data engineering

• Opportunity to work on technical challenges that may impact across geographies
• Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
• Opportunity to share your ideas on international platforms
• Sponsored Tech Talks & Hackathons
• Unlimited access to LinkedIn learning solutions
• Possibility to relocate to any EPAM office for short and long-term projects
• Focused individual development
• Benefit package:
  • Health benefits
  • Retirement benefits
  • Paid time off
  • Flexible benefits
• Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)