Lead Systems Engineer - Data DevOps/MLOps

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

Benefits offered by this job

Health benefits

Retirement benefits

Paid time off

LinkedIn learning access

Relocation to EPAM offices

Job summary

EPAM Systems, Inc. is seeking a Lead Systems Engineer with strong Data DevOps/MLOps expertise to build and maintain CI/CD pipelines for data integration and ML deployment. You will create scalable cloud infrastructure for training, processing, and serving models, and automate data workflows while collaborating with data scientists and engineers.

The role emphasizes security, monitoring, and reproducibility in production, with opportunities to advance across geographies and technologies.

Qualifications

• Bachelor's or Master's degree in Data Engineering, Computer Science or related field.
• 8+ years in MLOps, Data DevOps, or similar roles.
• Strong command of cloud platforms (GCP, AWS, Azure).
• Proficiency with infrastructure as code (e.g., Terraform, CloudFormation, Ansible).
• Hands-on with Kubernetes and Docker; experience with Databricks and Spark.
• Strong Python skills; familiarity with PyTorch, TensorFlow, Pandas.
• Experience with CI/CD tooling (GitHub Actions, GitLab CI/CD, Jenkins).

Responsibilities

• Build, launch, and maintain CI/CD pipelines for data and ML models.
• Create cloud-based infrastructure for ML training, processing, and serving.
• Automate data validation, transformation, and orchestration workflows.
• Collaborate with data scientists and engineers to productionize ML solutions.
• Improve monitoring, serving, and reliability in production environments.
• Ensure reproducibility, lineage, and data versioning in ML workflows.

Skills

Python programming

MLOps

Cloud platforms

CI/CD

Kubernetes & Docker

Data engineering knowledge

Communication

Education

Bachelor's or Master's degree in Data Engineering, Computer Science

Tools

Kubernetes

Docker

Terraform

Ansible

CloudFormation

Databricks

Apache Spark

Kubeflow

MLflow

GitHub Actions

Jenkins

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.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.ResponsibilitiesBuild, launch, and maintain CI/CD pipelines that enable smooth data integration and ML model deploymentCreate a solid cloud-based infrastructure foundation for training, processing, and serving machine learning modelsStreamline operations by automating essential workflows like data validation, transformation, and orchestrationWork alongside cross-functional teams, such as data scientists and engineers, to bring ML solutions into productionEnhance performance monitoring, model serving, and reliability within production environmentsMaintain reproducibility, lineage tracking, and data versioning throughout ML workflows and experimentsSpot and act on opportunities to boost the infrastructure's resilience, efficiency, and scalabilityApply strict security protocols to protect data while maintaining compliance with applicable regulationsTroubleshoot and fix technical problems within ML deployment workflows and data pipelinesRequirementsA Bachelor's or Master's degree in Data Engineering, Computer Science, or a related disciplineAt least 8 years working in MLOps, Data DevOps, or similar fieldsStrong command of cloud platforms including GCP, AWS, or AzureProficiency with Infrastructure as Code tools such as Ansible, CloudFormation, or TerraformHands-on knowledge of orchestration and containerization technologies like Kubernetes and DockerPractical experience using data processing frameworks such as Databricks and Apache SparkStrong Python skills along with familiarity with libraries like PyTorch, TensorFlow, and PandasFamiliarity with CI/CD tools including GitHub Actions, GitLab CI/CD, and JenkinsExperience working with MLOps platforms and version control systems such as Kubeflow, MLflow, and GitWorking knowledge of alerting and monitoring tools such as Grafana and PrometheusSolid ability to solve problems and make decisions independentlyStrong technical documentation and communication abilitiesNice to haveExperience with DataOps tools and methodologies such as dbt or AirflowFamiliarity with data governance platforms like CollibraExposure to Big Data technologies such as Hive or HadoopCertifications related to data engineering tools or cloud platformsWe 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.)