AI Devops Engineer

2 weeks ago

Pune, Maharashtra, India Verdantas Full time ₹ 15,00,000 - ₹ 25,00,000 per year

We at Verdantas are seeking an experienced and innovative
AI DevOps Engineer
to support the deployment, scaling, and monitoring of AI/ML models and infrastructure. This role bridges the gap between data science and operations, ensuring that machine learning workflows are automated, reproducible, and production ready.

Key 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.
  • 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.

Required Skills & Qualifications:

  • Bachelor's or master's degree in computer science, Engineering, or a related field.
  • 3+ years of experience in DevOps, with at least 1–2 years supporting AI/ML workflows.
  • 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 Qualifications:

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

Location and Work Set-up

· Pune, Maharashtra, India

· Work Mode: In Office

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