Lead Systems Engineer - Data DevOps/MLOps

About the Role

We are looking for a passionate and experienced Lead Systems Engineer specializing in Data DevOps and MLOps to spearhead innovation and enhance operational efficiency within our data and machine learning workflows. The position requires an individual capable of architecting and managing end-to-end CI/CD pipelines, automating critical data and model processing tasks, and collaborating closely with data science teams to deploy robust ML solutions into production.

Key Responsibilities

• Architect and implement CI/CD pipelines to enable seamless data integration along with deployment of machine learning models.
• Build and maintain scalable cloud infrastructure for ML training, serving, and data processing activities.
• Automate essential workflows including data validation, transformation, and orchestration to streamline operational tasks.
• Collaborate across teams, including data scientists and engineers, ensuring effective integration of ML models into production environments.
• Enhance model deployment processes by improving serving mechanisms, monitoring, and production reliability.
• Manage data versioning, track lineage, and ensure reproducibility of ML experiments and pipelines.
• Identify optimization opportunities to boost infrastructure scalability, efficiency, and fault tolerance.
• Implement stringent security protocols to protect data assets and maintain compliance with applicable regulations.
• Troubleshoot and resolve technical problems within data pipelines and machine learning deployment workflows.

Candidate Requirements

• Possess a Bachelor's or Master's degree in Computer Science, Data Engineering, or a related discipline.
• Have 8 or more years of professional experience in Data DevOps, MLOps, or similar domains.
• Demonstrated proficiency with cloud services platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with Infrastructure as Code tooling including Terraform, CloudFormation, or Ansible.
• Hands-on skills with containerization and orchestration technologies like Docker and Kubernetes.
• Familiarity with data processing frameworks, notably Apache Spark and Databricks.
• Strong programming ability in Python, including experience with libraries such as Pandas, TensorFlow, and PyTorch.
• Competence using CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions.
• Experience navigating version control and MLOps platforms, including Git, MLflow, and Kubeflow.
• Basic understanding of monitoring and alerting systems such as Prometheus and Grafana.
• Excellent problem-solving aptitude alongside independent decision-making strengths.
• Effective communication skills and ability to produce clear technical documentation.

Additional Preferred Qualifications

• Familiarity with DataOps methodologies and tools like Apache Airflow or dbt.
• Experience with data governance solutions such as Collibra.
• Knowledge of Big Data ecosystems including Hadoop or Hive.
• Certifications related to cloud platforms or data engineering toolsets.

About Epam Systems

Established in 1993, Epam Systems is a global leader in digital transformation and software engineering services, with a workforce spanning over 45 countries. Renowned for its engineering excellence, innovation, and strong culture, Epam delivers advanced digital platforms for enterprises, educational institutions, and healthcare that enhance connectivity, user experience, and societal impact. The company is recognized among Forbes Global 2000, the S&P 500 index, Fortune 1000 leaders, and top agencies by Ad Age and Consulting Magazine.