Senior Systems Engineer - Data DevOps/MLOps

TymblHub; Pune District; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

EPAM Systems in Pune, India, seeks a Senior Systems Engineer with deep Data DevOps/MLOps expertise to design and run large-scale data and ML pipelines in production.

You will build CI/CD pipelines, manage cloud infrastructure, and collaborate with data scientists, software engineers, and product teams to deliver reliable ML solutions. Emphasis on security, governance, and reproducibility with a strong focus on scalability and monitoring.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline.
• Minimum 5 years of experience in Data DevOps, MLOps, or comparable positions.
• Proficient with Azure, AWS, or GCP cloud platforms.
• Experience with Terraform, CloudFormation, or Ansible (IaC).
• Strong knowledge of Docker and Kubernetes.
• Experience with Apache Spark and Databricks.
• Proficient in Python and ML libraries (Pandas, TensorFlow, PyTorch).
• Familiar with Jenkins, GitLab CI/CD, GitHub Actions.
• Experience with Git, MLflow, Kubeflow.
• Knowledge of Prometheus and Grafana.
• Strong problem-solving and communication skills.

Responsibilities

• Build, launch, and oversee CI/CD pipelines supporting 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 ensure seamless ML model integration into production environments
• Improve model serving and monitoring capabilities to increase performance and reliability
• Oversee data versioning, lineage tracking, and reproducibility of ML experiments
• Continuously identify opportunities to improve deployment workflows, scalability, and infrastructure resilience
• Enforce robust security measures to protect data integrity and ensure regulatory compliance
• Diagnose and resolve problems across the entire data and ML pipeline lifecycle

Skills

Problem solving

Collaborative mindset

Communication

Analytical thinking

Attention to detail

Education

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

Tools

Azure

AWS

GCP

Terraform

CloudFormation

Ansible

Docker

Kubernetes

Apache Spark

Databricks

Python

Pandas

TensorFlow

PyTorch

Jenkins

GitLab CI/CD

GitHub Actions

Git

MLflow

Kubeflow

Prometheus

Grafana

Airflow

dbt

Collibra

Hadoop

Hive

Job description

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.

Responsibilities

• Build, launch, and oversee CI/CD pipelines supporting 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 ensure seamless ML model integration into production environments
• Improve model serving and monitoring capabilities to increase performance and reliability
• Oversee data versioning, lineage tracking, and reproducibility of ML experiments
• Continuously identify opportunities to improve deployment workflows, scalability, and infrastructure resilience
• Enforce robust security measures to protect data integrity and ensure regulatory compliance
• Diagnose and resolve problems across the entire data and ML pipeline lifecycle

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, or related discipline
• Minimum 5 years of experience in Data DevOps, MLOps, or comparable positions
• Skilled in cloud platforms such as Azure, AWS, or GCP
• Experienced with Infrastructure as Code tools like Terraform, CloudFormation, or Ansible
• Strong knowledge of containerization and orchestration tools, including Docker and Kubernetes
• Practical experience with data processing frameworks such as Apache Spark and Databricks
• Skilled in programming languages like Python, with familiarity in data manipulation and ML libraries such as Pandas, TensorFlow, and PyTorch
• Knowledgeable in CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions
• Experienced with version control systems and MLOps platforms including Git, MLflow, and Kubeflow
• Solid grasp of monitoring, logging, and alerting tools such as Prometheus and Grafana
• Strong problem-solving skills with the ability to perform well both independently and collaboratively
• Excellent communication and documentation abilities

Nice to have

• Experience with DataOps principles and tools like Airflow and dbt
• Understanding of data governance platforms such as Collibra
• Exposure to Big Data technologies including Hadoop and Hive
• Cloud or data engineering certifications

About the company

EPAM Systems delivers digital transformation and product engineering solutions, addressing complex challenges in diverse industries through innovative technology.

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