We're looking for a talented and dedicated Lead Systems Engineer with expertise in Data DevOps/MLOps to enhance innovation and efficiency throughout our data and machine learning operations.

Responsibilities

- Build, launch, and oversee CI/CD pipelines that enable smooth data integration and ML model deployment
- Create a strong infrastructure foundation for processing, training, and serving machine learning models through cloud-based platforms
- Streamline essential workflows including data validation, transformation, and orchestration to boost operational efficiency
- Partner with cross-functional teams, such as data scientists and engineers, to incorporate ML solutions into live production environments
- Enhance model serving capabilities, performance tracking, and reliability within production systems
- Maintain data versioning, lineage tracking, and reproducibility throughout ML experiments and workflows
- Spot and execute opportunities to boost scalability, efficiency, and resilience within the infrastructure
- Implement strict security protocols to protect data and maintain compliance with applicable regulations
- Troubleshoot and fix technical problems within data pipelines and ML deployment processes

Requirements

- A Bachelor's or Master's degree in Computer Science, Data Engineering, or a comparable field is required




- At least 8 years of hands-on experience in Data DevOps, MLOps, or similar fields
- Strong command of cloud platforms including Azure, AWS, or GCP
- Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible
- Expertise in containerization and orchestration solutions like Docker and Kubernetes
- Practical experience working with data processing frameworks such as Apache Spark and Databricks
- Strong Python skills along with familiarity using libraries like Pandas, TensorFlow, and PyTorch
- Working knowledge of CI/CD tools including Jenkins, GitLab CI/CD, and GitHub Actions
- Background using version control systems and MLOps platforms such as Git, MLflow, and Kubeflow
- Familiarity with monitoring and alerting solutions like Prometheus and Grafana
- Solid problem-solving abilities paired with the capacity to make independent decisions
- Strong communication skills along with the ability to produce transparent technical documentation

Nice to have

- Experience with DataOps methodologies and tools like Airflow or dbt
- Familiarity with data governance platforms such as Collibra
- Exposure to Big Data technologies including Hadoop or Hive
- Holds certifications in cloud platforms or data engineering tools

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