Description

As an AI Ops Engineer, you will play a key role in developing scalable AI products, focusing on building robust data architectures and optimizing ML delivery. Your work will involve managing cloud infrastructure and ensuring reliable AI operations, all while fostering innovation in a dynamic team environment.

Requirements

• •Ownership of end-to-end ML/AI infrastructure
• •Building self-service platforms and automated workflows
• •Experience in high-availability SaaS environments
• •Track record of designing scalable systems
• •Comfort with incident response and on-call rotations
• •Product mindset focusing on customer value
• •Clear communication and effective collaboration
• •Strong bias for automation and robust tooling

Tasks

• •Develop and maintain robust data architectures for high-volume SaaS applications
• •Build automated training pipelines and experiment tracking for reliable ML delivery
• •Operationalize LLMs from fine-tuning to high-performance serving and monitoring
• •Develop and maintain unified CI/CD pipelines for seamless code deployment
• •Architect scalable and cost-efficient AI workloads on AWS/Azure/GCP
• •Manage Kubernetes clusters and optimize autoscaling for AI systems
• •Deliver secure Docker-based containers optimized for ML and LLM workloads
• •Design ETL/ELT pipelines and integrate feature stores for data quality
• •Implement observability for AI operations, including logs and model drift detection
• •Embed security and compliance best practices into the infrastructure stack
• •Automate infrastructure and ML workflows using Python, Bash, and Terraform

Benefits