Description

We're working with a market-leading financial services powerhouse on this exciting opportunity to shape the future of transaction banking.

Jumpstart your career by building and optimizing sophisticated AI agent workflows and integrating LLMs into enterprise-grade tools. This is a rare chance for a high-potential graduate to gain hands-on experience with production-level Kubernetes, MLOps, and CI/CD pipelines within a massive scale environment.

The Role

Package and deploy trained AI/ML models into robust, production-ready Docker images.
Orchestrate large-scale deployments using Kubernetes pods to ensure high availability, resilience, and smart resource allocation.
Build and manage automated CI/CD pipelines for seamless model testing, deployment, and performance monitoring.
Drive environment management strategy, focusing on containerization, networking configuration, and production system health.
Implement advanced logging and monitoring tools to track real-time model performance and system metrics.

What You'll Need

A strong academic background or research experience specifically focused on Machine Learning and Artificial Intelligence.
Hands-on technical proficiency with Python and containerization tools like Docker and Kubernetes.
Familiarity with modern CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.
Exposure to major Cloud Platforms, specifically AWS, Azure, or GCP.
An analytical mindset with the methodological approach required to troubleshoot complex deployment and infrastructure issues.

What's On Offer

Competitive salary range of £30,000 - £38,000 based on experience.
Hybrid working model (2 days in-office) providing the perfect balance of collaboration and flexibility.
12-month fixed-term contract with significant scope for extension and long-term career progression.
Unrivaled professional support and development within a globally respected financial institution.

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