Junior ML Ops Engineer

As our portfolio of production AI systems continues to grow, so does the need for engineering excellence around reliability, scalability, and governance. To sustain this momentum, we are strengthening the team that ensures our models run seamlessly in production—delivering value every day while meeting the highest standards of compliance and observability.

The Data Science team is looking for a Junior MLOps Engineer to help improve and streamline the lifecycle of our AI models, from development to production. This role is particularly exciting because you will not be limited to a single domain; you will work across a diverse array of topics surrounding production-deployed models, gaining deep hands-on experience with the entire lifecycle of an AI product.

By joining the team, you will contribute to building the backbone that supports the bank's AI capabilities, ensuring efficiency and governance across the board.

As a Junior MLOps Engineer You Will:

• Automate Monitoring & Observability: Develop systems to automate the evaluation of deployed AI applications. You will work on improving observability for both classical Machine Learning models and Generative Models, ensuring we have real-time insights into performance and health.
• Build Deployment Platforms: Contribute to the development of an internal platform based on MLflow. You will help streamline the developer experience by creating tools for model and agent versioning, packaging, and seamless deployment onto our internal infrastructure.
• Orchestrate Pipelines: Design, optimize, and orchestrate complex data and training pipelines using Argo Workflows, ensuring that our model training processes are reproducible and efficient.
• Enforce AI Governance: Help build a governance platform that acts as a central control plane, ensuring that all deployed AI applications strictly adhere to company regulations and compliance standards.