Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems; Pune District; Sur place; INR 1 200 000 - 1 800 000; Plein temps

Avantages offerts par ce poste

Health benefits

Retirement benefits

Paid time off

Flexible benefits

LinkedIn learning access

Tech Talks & Hackathons

Relocate to EPAM offices

Résumé du poste

EPAM Systems in Pune, India, seeks a Senior Data DevOps/MLOps Engineer to design and manage data pipelines, ML model deployment, and scalable CI/CD workflows. You will build cloud infrastructure, automate validation and orchestration, and collaborate with data scientists and engineers to deliver robust, production-ready ML solutions.

The role emphasizes data governance, security, and reliable monitoring, with opportunities to work on large-scale projects across geographies and platforms.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.
• Minimum 5 years of experience in Data DevOps, MLOps, or comparable positions.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Proficient with Infrastructure as Code tools like Terraform, CloudFormation, or Ansible.
• Strong knowledge of containers and orchestration (Docker, Kubernetes).
• Experience with data processing frameworks (Apache Spark, Databricks).
• Proficient in Python with ML libraries (Pandas, TensorFlow, PyTorch).
• Experience with CI/CD tools (Jenkins, GitLab CI/CD, GitHub Actions).
• Experience with MLOps tools (Git, MLflow, Kubeflow).
• Knowledge of monitoring/logging tools (Prometheus, Grafana).
• Familiarity with Airflow, dbt, and data governance concepts.

Responsabilités

• 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.
• Collaborate with data scientists, software engineers, and product teams for ML model productionization.
• Improve model serving, monitoring, and reliability.
• Oversee data versioning, lineage, and reproducibility of ML experiments.
• Ensure data security and regulatory compliance across pipelines.
• Diagnose and resolve issues across the data/ML lifecycle.

Connaissances

Data DevOps

MLOps

CI/CD pipelines

Cloud platforms

Python

Communication

Formation

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

Outils

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Apache Spark

Databricks

Jenkins

GitLab CI/CD

GitHub Actions

MLflow

Kubeflow

Description du poste

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.)