Description

Own MLOps and LLMOps workflows, CI/CD pipelines, and production infrastructure for machine learning and Generative AI applications.

This role is on-site.

Responsibilities

• Design and optimize CI/CD pipelines for ML and GenAI applications.
• Deploy, monitor, and manage ML and LLM models in production using MLflow.
• Build scalable infrastructure for model release management and observability.
• Implement Infrastructure as Code (Terraform) and automation for platform operations.
• Collaborate with data science and engineering teams to standardize enterprise AI practices.

Required Skills

• 5+ years of experience in MLOps or LLMOps platform engineering.
• Strong hands-on experience with Databricks and MLflow.
• Proficiency in Azure and/or GCP cloud platforms.
• Expertise in Kubernetes, Docker, and Terraform.
• Proven track record building and scaling CI/CD pipelines.
• Experience supporting GenAI / LLM applications in production.
• Knowledge of model governance, observability, and lifecycle management.

Preferred Skills

• Experience with enterprise-scale AI/ML platforms.
• Exposure to production-grade LLM monitoring frameworks.
• Proven ability to lead technical initiatives and define engineering standards.

Key Skills

Education

Bachelor's degree