We're looking for a talented and dedicated Lead Systems Engineer who brings Data DevOps/MLOps expertise to help drive innovation and efficiency throughout our data and machine learning operations.

Responsibilities

- Build, launch, and maintain CI/CD pipelines that enable smooth data integration and ML model deployment

- Create a solid cloud-based infrastructure foundation for training, processing, and serving machine learning models

- Streamline operations by automating essential workflows like data validation, transformation, and orchestration

- Work alongside cross-functional teams, such as data scientists and engineers, to bring ML solutions into production

- Enhance performance monitoring, model serving, and reliability within production environments

- Maintain reproducibility, lineage tracking, and data versioning throughout ML workflows and experiments

- Spot and act on opportunities to boost the infrastructure's resilience, efficiency, and scalability

- Apply strict security protocols to protect data while maintaining compliance with applicable regulations

- Troubleshoot and fix technical problems within ML deployment workflows and data pipelines

Requirements

- A Bachelor's or Master's degree in Data Engineering, Computer Science, or a related discipline





- At least 8 years working in MLOps, Data DevOps, or similar fields

- Strong command of cloud platforms including GCP, AWS, or Azure

- Proficiency with Infrastructure as Code tools such as Ansible, CloudFormation, or Terraform

- Hands-on knowledge of orchestration and containerization technologies like Kubernetes and Docker

- Practical experience using data processing frameworks such as Databricks and Apache Spark

- Strong Python skills along with familiarity with libraries like PyTorch, TensorFlow, and Pandas

- Familiarity with CI/CD tools including GitHub Actions, GitLab CI/CD, and Jenkins

- Experience working with MLOps platforms and version control systems such as Kubeflow, MLflow, and Git

- Working knowledge of alerting and monitoring tools such as Grafana and Prometheus

- Solid ability to solve problems and make decisions independently

- Solid technical documentation and communication abilities

Nice to have

- Experience with DataOps tools and methodologies such as dbt or Airflow

- Familiarity with data governance platforms like Collibra

- Exposure to Big Data technologies such as Hive or Hadoop

- Certifications related to data engineering tools or cloud platforms

📌 Lead Systems Engineer - Data DevOps/MLOps (Pune)
🏢 EPAM Systems
📍 Pune