EPAM Systems
Website:
epam.com
Company:
https://www.linkedin.com/company/epam-systems
Seniority: Mid-Senior level
Industries: Software Development and IT Services and IT Consulting
Job details:
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
- Design CI/CD pipelines for data integration and machine learning model deployment
- Deploy and maintain infrastructure for data processing and model training using cloud services
- Automate processes like data validation, transformation, and workflow orchestration
- Coordinate with data scientists, software engineers, and product teams to integrate ML models into production environments
- Enhance performance and reliability by optimizing model serving and monitoring processes
- Ensure data versioning, lineage tracking, and reproducibility across ML experiments
- Identify improvements for deployment processes, scalability, and infrastructure resilience
- Implement security measures to safeguard data integrity and maintain compliance
- Resolve issues in the data and ML pipeline lifecycle
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
- 5 or more years of experience in Data DevOps, MLOps, or related professions
- Proficiency in cloud platforms such as Azure, AWS, or GCP
- Background in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible
- Expertise in containerization and orchestration tools such as Docker and Kubernetes
- Skills in using data processing frameworks like Apache Spark or Databricks
- Proficiency in Python, with familiarity with data manipulation and ML libraries such as Pandas, TensorFlow, or PyTorch
- Familiarity with CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions
- Knowledge of version control systems, such as Git, and MLOps platforms like MLflow or Kubeflow
- Understanding of monitoring, logging, and alerting systems like Prometheus or Grafana
- Strong problem-solving abilities with the capability to work both independently and collaboratively
- Effective communication and documentation skills
Nice to have
- Familiarity with DataOps practices and tools like Airflow or dbt
- Understanding of data governance frameworks and tools like Collibra
- Knowledge of Big Data technologies such as Hadoop or Hive
- Credentials in cloud platforms or data engineering activities
Click on Apply to know more.
