AI Engineer

Xcede; Greater London; Sur place; GBP 80 000 - 110 000; Plein temps

Résumé du poste

Xcede is seeking an AI Engineer to join their AI unit within a data-driven insurance client. You will build and deploy production-level models with a focus on LLMs and RAGs, collaborating with business teams to translate requirements into scalable AI solutions.

The role emphasizes end-to-end responsibilities, shipping AI to production, and hands-on deployment of ML and LLM models in real-world projects.

Qualifications

• Several years of commercial experience in a Data Science role building statistical and machine learning models.
• Built and deployed machine learning models in production.
• Excellent use of Python.
• Experience with NLP, LLMs and RAGs is highly valued.
• CI/CD and MLOps experience is valued.
• Databricks experience is valued.

Responsabilités

• Develop and deploy production-level models for commercial projects with a focus on LLMs and RAGs.
• Collaborate with cross-functional teams to understand business requirements and identify deployment opportunities for statistical models.
• Build production-grade ML and LLM models and be hands-on in deployment.
• Evaluate and select appropriate ML techniques to solve commercial challenges.

Connaissances

Python

NLP/LLMs/RAGs

Production ML deployment

Data science

CI/CD / MLOps

Databricks

Outils

Databricks

Description du poste

Xcede’s Data-driven Insurance client with an excellent Data Science, ML Engineering and MLOps team is hiring for an AI Engineer to join their AI unit. The organisation have been building commercially successful Data Science products for years, and are now pushing further into Generative AI with multiple LLM-based projects in production across the company.

In this role you will be responsible for building and deploying production-level models for a breadth of interesting commercial projects. The role is end-to-end focused. Your responsibilities as an AI Engineer will include, but not be limited to:

• Developing and deploying predictive models and algorithms for commercial projects with a particular focus on LLMs and RAGs.
• Collaborate with cross-functional commercial and business teams, to understand business requirements and identify opportunities for deploying statistical models.
• Building production level Machine Learning & LLM models and be hands on in deployment.
• Evaluating and select appropriate machine learning techniques and algorithms for solving commercial challenges.

\"The most important thing is a track record of shipping AI to production for real end-users, not just proofs of concept or personal projects. This doesn't have to be in one specific area - experience with agents, document retrieval and evaluation is ideal. Also the ability to articulate why - what was the business context, what was the impact and why was AI the appropriate technology in that scenario.\"

YOUR SKILLS & EXPERIENCE

A successful AI Engineer will have the following:

• Have a number of years of commercial experience in a Data Science role building statistical & machine learning models.
• Have built and deployed machine learning models in production.
• Excellent use of Python
• Particular experience in NLP, LLMs, and RAGs are highly prized given the focus on these projects.
• CI/CD & MLOps experience is valued
• Databricks experience is valued