We are looking for a skilled and motivated Senior Systems Engineer with expertise in Data DevOps/MLOps to join our team.
The ideal candidate must possess a strong understanding of data engineering, automation for data pipelines, and operationalizing machine learning models. This role requires a collaborative professional capable of building, deploying, and managing scalable data and ML pipelines that meet business objectives.
Responsibilities
- Design, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment
- Build and maintain infrastructure for data processing and model training using cloud-native tools and services
- Automate processes for data validation, transformation, and workflow orchestration
- Coordinate with data scientists, software engineers, and product teams to enable seamless integration of ML models into production
- Optimize performance and reliability of model serving and monitoring solutions
- Manage data versioning, lineage tracking, and reproducibility for ML experiments
- Identify opportunities to enhance scalability, streamline deployment processes, and improve infrastructure resilience
- Implement security measures to safeguard data integrity and ensure regulatory compliance
- Diagnose and resolve issues throughout the data and ML pipeline lifecycle
Requirements
- 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 like Azure, AWS, or GCP
- Competency in using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
- Expertise in containerization and orchestration technologies like Docker and Kubernetes
- Background in data processing frameworks such as Apache Spark or Databricks
- Skills in Python programming, with proficiency in data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
- Familiarity with CI/CD tools, including Jenkins, GitLab CI/CD, or GitHub Actions
- Understanding of version control tools like Git and MLOps platforms such as MLflow or Kubeflow
- Knowledge of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana)
- Strong problem-solving skills and ability to contribute both independently and within a team
- Excellent communication skills and attention to documentation
Nice to have
- Knowledge of DataOps practices and tools like Airflow or dbt
- Understanding of data governance concepts and platforms such as Collibra
- Background in Big Data technologies like Hadoop or Hive
- Qualifications in cloud platforms or data engineering
We offer
- 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.)
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.
