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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: Chennai, & 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 dedicated and proficient Senior Systems Engineer with extensive Data DevOps/MLOps knowledge to enhance our team.

The ideal candidate should possess a comprehensive knowledge of data engineering, data pipeline automation, and machine learning model operationalization. The role demands a cooperative professional skilled in designing, deploying, and managing extensive data and ML pipelines in alignment with organizational objectives.

What you would do

* Develop, deploy, and manage Continuous Integration/Continuous Deployment (CI/CD) pipelines for data integration and machine learning model deployment

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

* Set up and sustain infrastructure for data processing and model training through cloud-based resources and services

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

* Work closely with data scientists, software engineers, and product teams for a smooth integration of ML models into production

* Enhance model serving and monitoring to boost performance and dependability

* Manage data versioning, lineage tracking, and the reproducibility of ML experiments

* Actively search for enhancements in deployment processes, scalability, and infrastructure resilience

* Implement stringent security protocols to safeguard data integrity and compliance with regulations

* Troubleshoot and solve issues throughout 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+ years of experience in Data DevOps, MLOps, or similar roles

* 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 technologies including Docker and Kubernetes

* Hands-on experience with data processing frameworks such as Apache Spark and Databricks

* Proficiency in programming languages including Python with an understanding of data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch

* Familiarity with CI/CD tools including Jenkins, GitLab CI/CD, and GitHub Actions

* Experience with version control tools and MLOps platforms such as Git, MLflow, and Kubeflow

* Strong understanding of monitoring, logging, and alerting systems including Prometheus and Grafana

* Excellent problem-solving abilities with capability to work independently and in teams

* Strong skills in communication and documentation

* Background in DataOps concepts and tools such as Airflow and dbt

* Knowledge of data governance platforms like Collibra

* Familiarity with Big Data technologies including Hadoop and Hive

* Certifications in cloud platforms or data engineering

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.)