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 detail-oriented and motivated Senior Systems Engineer with a strong focus on Data DevOps/MLOps to join our team.
The ideal candidate should possess a deep understanding of data engineering, automation of data pipelines, and integration of machine learning models into operational environments. This role is for a collaborative professional adept at building, deploying, and managing scalable data and ML pipelines aligned with strategic objectives.
Responsibilities
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Design CI/CD pipelines for data integration and machine learning model deployment
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Deploy and maintain infrastructure for data processing and model training using cloud services
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Automate processes like data validation, transformation, and workflow orchestration
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Coordinate with data scientists, software engineers, and product teams to integrate ML models into production environments
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Enhance performance and reliability by optimizing model serving and monitoring processes
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Ensure data versioning, lineage tracking, and reproducibility across ML experiments
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Identify improvements for deployment processes, scalability, and infrastructure resilience
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Implement security measures to safeguard data integrity and maintain compliance
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Resolve issues in the data and ML pipeline lifecycle
Requirements
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Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
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5 or more years of experience in Data DevOps, MLOps, or related professions
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Proficiency in cloud platforms such as Azure, AWS, or GCP
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Background in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible
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Expertise in containerization and orchestration tools such as Docker and Kubernetes
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Skills in using data processing frameworks like Apache Spark or Databricks
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Proficiency in Python, with familiarity with data manipulation and ML libraries such as Pandas, TensorFlow, or PyTorch
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Familiarity with CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions
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Knowledge of version control systems, such as Git, and MLOps platforms like MLflow or Kubeflow
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Understanding of monitoring, logging, and alerting systems like Prometheus or Grafana
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Strong problem-solving abilities with the capability to work both independently and collaboratively
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Effective communication and documentation skills
Nice to have
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Familiarity with DataOps practices and tools like Airflow or dbt
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Understanding of data governance frameworks and tools like Collibra
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Knowledge of Big Data technologies such as Hadoop or Hive
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Credentials in cloud platforms or data engineering activities
We offer
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Opportunity to work on technical challenges that may impact across geographies
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Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
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Opportunity to share your ideas on international platforms
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Sponsored Tech Talks & Hackathons
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Unlimited access to LinkedIn learning solutions
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Possibility to relocate to any EPAM office for short and long-term projects
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Focused individual development
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Benefit package:
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Health benefits
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Retirement benefits
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Paid time off
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Flexible benefits
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Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)
