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AI Devops Engineer

AI Devops Engineer

verdantas
5-8 Years
Not Disclosed

This job is no longer accepting applications

Job Description

Join Verdantas – A Top #ENR 81 Firm!

We at Verdantas, looking for AI Devops Engineer to join our team

The AI Devops Engineer will design and manage scalable, secure DevOps infrastructure and CI/CD pipelines that enable efficient application deployment, automation, monitoring, and operations across cloud environments.

Responsibilities:

  • Design and maintain CI/CD pipelines for AI/ML model training, testing, and deployment.
  • Automate infrastructure provisioning using Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
  • Manage containerized environments using Docker and Kubernetes, including GPU orchestration.
  • Collaborate with data scientists to productionize ML models using MLOps best practices.
  • Monitor model performance and system health using tools like Prometheus, Grafana, or ELK Stack.
  • Experience with data pipeline orchestration tools (Airflow, Prefect, or Luigi).

Preferred

  • Implement model versioning, experiment tracking, and reproducibility using tools like MLflow, DVC, or Kubeflow.
  • Ensure security, compliance, and scalability of AI workloads on cloud platforms (AWS, Azure, GCP).
  • Optimize compute resource usage and cost for training and inference workloads.

Technical Skills:

  • Proficiency in scripting languages (Python, Bash) and automation tools.
  • Experience with ML platforms and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
  • Strong knowledge of containerization (Docker) and orchestration (Kubernetes).
  • Familiarity with CI/CD tools (Jenkins, GitHub Actions, GitLab CI).
  • Experience with cloud infrastructure (AWS, Azure, or GCP), especially GPU-based workloads.

Preferred

  • Experience with data pipeline orchestration tools (Airflow, Prefect, or Luigi).
  • Understanding model monitoring, drift detection, and retraining strategies.
  • Knowledge of data governance, security, and compliance in AI systems.
  • Certifications in cloud platforms or MLOps tools.

Experience: 5-8 Years

Location and Work Set-up

  • Pune, Maharashtra, India
  • Work Mode: In Office

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