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Senior Systems Engineer - Data DevOps/MLOps

at Epam

India: Hyderabad, senior, 5+ years

seen 5d ago

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  • Airflow
  • GitLab CI/CD
  • MLflow
  • Prometheus
  • Grafana
  • Kubeflow
  • PyTorch
  • GitHub Actions
  • Terraform
  • Docker
  • AWS
  • Python
  • TensorFlow
  • Azure
  • Collibra
  • CloudFormation
  • Hadoop
  • Apache Spark
  • Jenkins
  • Hive
  • Git
  • GCP
  • Ansible
  • Pandas
  • dbt
  • Databricks
  • Kubernetes

About the role

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Senior Systems Engineer - Data DevOps/MLOps

Office in India: Coimbatore, & 5 others

Data DevOps& 19 others

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Senior Systems Engineer - Data DevOps/MLOps

Location-specific conditions & benefits*

India: Hyderabad

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Senior Systems Engineer - Data DevOps/MLOps\ \ India, Hyderabad\ \ \ \ \ \

Senior Systems Engineer - Data DevOps/MLOps\ \ India, Hyderabad\ \ \ \ \ \

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Location-specific conditions & benefits*

India: Hyderabad

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 are looking for a detail-oriented and motivated Senior Systems Engineer with a strong focus on Data DevOps/MLOps to join our team.

The ideal candidate should possess a deep understanding of data engineering, automation of data pipelines, and integration of machine learning models into operational environments. This role is for a collaborative professional adept at building, deploying, and managing scalable data and ML pipelines aligned with strategic objectives.

What you would do

* Design CI/CD pipelines for data integration and machine learning model deployment

Read from careers.epam.com, last seen 5d ago.

* Deploy and maintain infrastructure for data processing and model training using cloud services

* Automate processes like data validation, transformation, and workflow orchestration

* Coordinate with data scientists, software engineers, and product teams to integrate ML models into production environments

* Enhance performance and reliability by optimizing model serving and monitoring processes

* Ensure data versioning, lineage tracking, and reproducibility across ML experiments

* Identify improvements for deployment processes, scalability, and infrastructure resilience

* Implement security measures to safeguard data integrity and maintain compliance

* Resolve issues in the data and ML pipeline lifecycle

What they are looking for

* Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field

* 5 or more years of experience in Data DevOps, MLOps, or related professions

* Proficiency in cloud platforms such as Azure, AWS, or GCP

* Background in Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Ansible

* Expertise in containerization and orchestration tools such as Docker and Kubernetes

* Skills in using data processing frameworks like Apache Spark or Databricks

* Proficiency in Python, with familiarity with data manipulation and ML libraries such as Pandas, TensorFlow, or PyTorch

* Familiarity with CI/CD tools like Jenkins, GitLab CI/CD, or GitHub Actions

* Knowledge of version control systems, such as Git, and MLOps platforms like MLflow or Kubeflow

* Understanding of monitoring, logging, and alerting systems like Prometheus or Grafana

* Strong problem-solving abilities with the capability to work both independently and collaboratively

* Effective communication and documentation skills

* Familiarity with DataOps practices and tools like Airflow or dbt

* Understanding of data governance frameworks and tools like Collibra

* Knowledge of Big Data technologies such as Hadoop or Hive

* Credentials in cloud platforms or data engineering activities

What comes with it

Opportunity to work on technical challenges that may impact across geographies

Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications

Opportunity to share your ideas on international platforms

Sponsored Tech Talks & Hackathons

Unlimited access to LinkedIn learning solutions

Possibility to relocate to any EPAM office for short and long-term projects

Focused individual development

* Health benefits * Retirement benefits * Paid time off * Flexible benefits

Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)