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 Systems Engineer with extensive Data DevOps/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.
Responsibilities
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Develop, deploy, and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for data integration and machine learning model deployment
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Set up and sustain infrastructure for data processing and model training through cloud-based resources and services
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Automate processes for data validation, transformation, and workflow orchestration
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Work closely with data scientists, software engineers, and product teams for a smooth integration of ML models into production
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Enhance model serving and monitoring to boost performance and dependability
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Manage data versioning, lineage tracking, and the reproducibility of ML experiments
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Actively search for enhancements in deployment processes, scalability, and infrastructure resilience
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Implement stringent security protocols to safeguard data integrity and compliance with regulations
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Troubleshoot and solve issues throughout 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+ years of experience in Data DevOps, MLOps, or similar roles
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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 technologies including Docker and Kubernetes
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Hands-on experience with data processing frameworks such as Apache Spark and Databricks
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Proficiency in programming languages including Python with an understanding of data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
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Familiarity with CI/CD tools including Jenkins, GitLab CI/CD, and GitHub Actions
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Experience with version control tools and MLOps platforms such as Git, MLflow, and Kubeflow
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Strong understanding of monitoring, logging, and alerting systems including Prometheus and Grafana
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Excellent problem-solving abilities with capability to work independently and in teams
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Strong skills in communication and documentation
Nice to have
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Background in DataOps concepts and tools such as Airflow and dbt
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Knowledge of data governance platforms like Collibra
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Familiarity with Big Data technologies including Hadoop and Hive
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Certifications in cloud platforms or data engineering
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.)
