Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems; Bengaluru; On-site; INR 3,500,000 - 6,500,000; Full time

Benefits offered by this job

Health benefits

Retirement benefits

Paid time off

Flexible benefits

Sponsored Tech Talks & Hackathons

LinkedIn learning access

Relocation to EPAM offices

Job summary

EPAM Systems, Inc. in Bengaluru seeks a Senior Systems Engineer with deep Data DevOps/MLOps expertise to design and run end-to-end ML pipelines and CI/CD for data workflows, along with scalable cloud infrastructure.

You’ll collaborate with data scientists and software engineers to productionize models, ensure security/compliance, and monitor deployments using Prometheus/Grafana. 5+ years in similar roles is required.

Qualifications

• Bachelor's or Master's in Computer Science, Data Engineering, or related discipline.
• Minimum 5 years of experience in Data DevOps, MLOps, or comparable positions.
• Cloud platforms: Azure, AWS, or GCP.
• Infrastructure as Code: Terraform, CloudFormation, or Ansible.
• Containerization/orchestration: Docker and Kubernetes.
• Data processing: Apache Spark and Databricks.
• Programming: Python with Pandas, TensorFlow, PyTorch.
• CI/CD: Jenkins, GitLab CI/CD, and GitHub Actions.
• Experience with Git, MLflow, Kubeflow.
• Monitoring: Prometheus and Grafana.
• DataOps: Airflow and dbt.
• Hadoop and Hive familiarity.
• Nice-to-have: cloud/data engineering certifications.
• Excellent communication and collaboration skills.

Responsibilities

• Build, launch, and oversee CI/CD pipelines for data integration and ML model rollout.
• Establish and maintain cloud-based infrastructure for data processing and model training.
• Streamline data validation, transformation, and workflow orchestration through automation.
• Partner with data scientists, software engineers, and product teams to productionize ML models.
• Improve model serving and monitoring for performance and reliability.
• Oversee data versioning, lineage, and reproducibility of experiments.
• Identify opportunities to improve deployment workflows, scalability, and resilience.
• Enforce robust security measures to protect data integrity and regulatory compliance.
• Diagnose and resolve problems across the data/ML pipeline lifecycle.

Skills

Cloud platforms (Azure/AWS/GCP)

Docker

Kubernetes

Python

Pandas

TensorFlow

PyTorch

CI/CD tools (Jenkins/GitLab/GitHub)

MLflow

Kubeflow

Prometheus

Grafana

Airflow/dbt (DataOps)

Terraform/CloudFormation/Ansible

Databricks

Apache Spark

Git (version control)

Education

Bachelor's or Master's in CS/Data Eng

Tools

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Job description

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.Our team is seeking a skilled and committed Senior Systems Engineer with deep expertise in Data DevOps/MLOps to join our organization.The successful applicant should have thorough understanding of data engineering, automated data pipelines, and deployment of machine learning models in production. This position requires a collaborative individual capable of architecting, implementing, and overseeing large-scale data and ML pipelines that support company goals.ResponsibilitiesBuild, launch, and oversee CI/CD pipelines supporting data integration and ML model rolloutEstablish and maintain cloud-based infrastructure for data processing and model trainingStreamline data validation, transformation, and workflow orchestration through automationPartner with data scientists, software engineers, and product teams to ensure seamless ML model integration into production environmentsImprove model serving and monitoring capabilities to increase performance and reliabilityOversee data versioning, lineage tracking, and reproducibility of ML experimentsContinuously identify opportunities to improve deployment workflows, scalability, and infrastructure resilienceEnforce robust security measures to protect data integrity and ensure regulatory complianceDiagnose and resolve problems across the entire data and ML pipeline lifecycleRequirementsBachelor's or Master's degree in Computer Science, Data Engineering, or related disciplineMinimum 5 years of experience in Data DevOps, MLOps, or comparable positionsSkilled in cloud platforms such as Azure, AWS, or GCPExperienced with Infrastructure as Code tools like Terraform, CloudFormation, or AnsibleStrong knowledge of containerization and orchestration tools, including Docker and KubernetesPractical experience with data processing frameworks such as Apache Spark and DatabricksSkilled in programming languages like Python, with familiarity in data manipulation and ML libraries such as Pandas, TensorFlow, and PyTorchKnowledgeable in CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub ActionsExperienced with version control systems and MLOps platforms including Git, MLflow, and KubeflowSolid grasp of monitoring, logging, and alerting tools such as Prometheus and GrafanaStrong problem-solving skills with the ability to perform well both independently and collaborativelyExcellent communication and documentation abilitiesNice to haveExperience with DataOps principles and tools like Airflow and dbtUnderstanding of data governance platforms such as CollibraExposure to Big Data technologies including Hadoop and HiveCloud or data engineering certificationsWe offerOpportunity to work on technical challenges that may impact across geographiesVast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certificationsOpportunity to share your ideas on international platformsSponsored Tech Talks & HackathonsUnlimited access to LinkedIn learning solutionsPossibility to relocate to any EPAM office for short and long-term projectsFocused individual developmentBenefit package:Health benefitsRetirement benefitsPaid time offFlexible benefitsForums to explore beyond work passion (CSR, photography, painting, sports, etc.)