Senior Systems Engineer - Data DevOps/MLOps

EPAM Systems

4 years

0 Lacs

hyderabad telangana india

Posted:1 day ago| Platform:

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Skills Required

data devops engineering automation learning collaborative ml design integration model processing training automate workflow software reliability monitoring versioning tracking scalability deployment security integrity resolve pipeline azure aws code terraform containerization orchestration docker apache spark python programming tensorflow jenkins gitlab github git mlflow logging communication airflow governance hadoop

Work Mode

On-site

Job Type

Full Time

Job Description

Senior Systems Engineer

The ideal candidate must possess a strong understanding of data engineering, automation for data pipelines, and operationalizing machine learning models. This role requires a collaborative professional capable of building, deploying, and managing scalable data and ML pipelines that meet business objectives.

Responsibilities

Design, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment
Build and maintain infrastructure for data processing and model training using cloud-native tools and services
Automate processes for data validation, transformation, and workflow orchestration
Coordinate with data scientists, software engineers, and product teams to enable seamless integration of ML models into production
Optimize performance and reliability of model serving and monitoring solutions
Manage data versioning, lineage tracking, and reproducibility for ML experiments
Identify opportunities to enhance scalability, streamline deployment processes, and improve infrastructure resilience
Implement security measures to safeguard data integrity and ensure regulatory compliance
Diagnose and resolve issues throughout the data and ML pipeline lifecycle

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
4+ years of experience in Data DevOps, MLOps, or similar roles
Proficiency in cloud platforms like Azure, AWS, or GCP
Competency in using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible
Expertise in containerization and orchestration technologies like Docker and Kubernetes
Background in data processing frameworks such as Apache Spark or Databricks
Skills in Python programming, with proficiency in data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch
Familiarity with CI/CD tools, including Jenkins, GitLab CI/CD, or GitHub Actions
Understanding of version control tools like Git and MLOps platforms such as MLflow or Kubeflow
Knowledge of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana)
Strong problem-solving skills and ability to contribute both independently and within a team
Excellent communication skills and attention to documentation

Nice to have

Knowledge of DataOps practices and tools like Airflow or dbt
Understanding of data governance concepts and platforms such as Collibra
Background in Big Data technologies like Hadoop or Hive
Qualifications in cloud platforms or data engineering

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