About the Role
Outside IR35 £200 - £300
Initial 6 month contract - high possibility of 18 months
Hybrid work
Our client is hiring a Data Scientist – AI/ML Engineer to join our Core AI Services team. You’ll be at the forefront of designing and scaling cloud-native AI platform services and APIs that enable enterprise-wide AI adoption. Working within a collaborative Scrum team, you’ll help build secure, reliable, and production-grade AI solutions that are ethical, scalable, and future-ready.
This is a unique opportunity to work on cutting-edge AI systems in a global R&D environment, contributing to the development of trustworthy AI services.
About the Role:
DataBuzz is hiring a Data Scientist - AI/ML Engineer to join our Core AI Services team. You'll design and scale cloud-native AI platform services and APIs that power enterprise AI adoption. Working in a Scrum team with developers, architects, and data scientists, you'll build secure, reliable, and production-grade AI solutions. If you're passionate about solving complex challenges and advancing cutting-edge AI, this role is for you.
Skills & Experience:
* 7+ Years of experience as a Data Scientist or in a similar role.
* Strong programming skills in Python are essential, including libraries such as pandas, scikit-learn, TensorFlow, or PyTorch.
* Experience working with Large Language Models (LLMs).
* Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling
* Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A)
* Experience in working with various ML algorithms (regression, classification, clustering, deep learning)
* Familiarity with Azure cloud platform.
* Strong problem-solving skills and the ability to explain technical concepts to non-technical audiences are important.
What You'll Do:
* Build scalable, fault-tolerant cloud-native services on Microsoft Azure.
* Develop secure, well-documented APIs and SDKs for developers inside and outside the organisation.
* Collaborate with teams to deliver end-to-end data pipelines, orchestration, and service APIs.
* Embed security best practices around authentication, authorization, and data privacy.
* Take part in design reviews, code reviews, and architecture discussions to ensure excellence.
* Deploy and manage AI models and tooling for enterprise-scale adoption.
* Mentor junior developers and foster a culture of continuous learning and innovation.