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 seeking a skilled and passionate Lead Systems Engineer with Data DevOps/MLOps expertise to drive innovation and efficiency across our data and machine learning operations.
Responsibilities
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Design, deploy, and manage CI/CD pipelines for seamless data integration and ML model deployment
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Establish robust infrastructure for processing, training, and serving machine learning models using cloud-based solutions
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Automate critical workflows such as data validation, transformation, and orchestration for streamlined operations
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Collaborate with cross-functional teams, including data scientists and engineers, to integrate ML solutions into production environments
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Improve model serving, performance monitoring, and reliability in production ecosystems
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Ensure data versioning, lineage tracking, and reproducibility across ML experiments and workflows
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Identify and implement opportunities to improve scalability, efficiency, and resilience of the infrastructure
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Enforce rigorous security measures to safeguard data and ensure compliance with relevant regulations
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Debug and resolve technical issues in data pipelines and ML deployment workflows
Requirements
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Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
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8+ years of experience in Data DevOps, MLOps, or related disciplines
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Expertise in cloud platforms such as Azure, AWS, or GCP
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Skills in Infrastructure as Code tools like Terraform, CloudFormation, or Ansible
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Proficiency in containerization and orchestration technologies such as Docker and Kubernetes
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Hands-on experience with data processing frameworks including Apache Spark and Databricks
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Proficiency in Python with familiarity with libraries including Pandas, TensorFlow, and PyTorch
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Knowledge of CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions
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Experience with version control systems and MLOps platforms including Git, MLflow, and Kubeflow
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Understanding of monitoring and alerting tools like Prometheus and Grafana
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Strong problem-solving and independent decision-making capabilities
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Effective communication and technical documentation skills
Nice to have
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Background in DataOps methodologies and tools such as Airflow or dbt
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Knowledge of data governance platforms like Collibra
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Familiarity with Big Data technologies such as Hadoop or Hive
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Showcase of certifications in cloud platforms or data engineering tools
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.)
