Senior Systems Engineer - Data DevOps/MLOps

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:•

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.)