ML Engineer

Introduction

As an ML Engineer, you will play a key role in building and improving Client's AI Platform. Your primary responsibility will be designing and implementing the core REST API that powers the platform. You will collaborate with other IT teams to ensure the platform is reliable, secure, and easy-to-use for teams.

Responsibilities

• Design and implement core REST API using Python and FastAPI
• Collaborate with other IT teams to deliver a reliable and secure AI platform
• Work on infrastructure automation using tools like Terraform
• Utilize Git, GitHub Actions, CI/CD pipelines, and automated testing for efficient development
• Troubleshoot, debug, and handle errors effectively
• Implement logging, monitoring, and observability practices
• Collaborate with security, cloud, and networking teams to meet enterprise requirements
• Produce maintainable, well-tested code and clear technical documentation
• Communicate architecture decisions and technical trade-offs to stakeholders

Requirements

Required Skills:

• Python
• Asynchronous REST API development using FastAPI
• Git and GitHub Actions
• CI/CD pipelines and automated testing
• MLOps

Preferred Skills:

• Experience with Microsoft Azure including identity and access management, secrets management, and private networking
• Familiarity with Azure Machine Learning, Microsoft Foundry, and MLOps practices
• Experience in energy, utilities, or regulated enterprise environments
• Hands-on experience with Infrastructure as Code using Terraform