Data Scientist

Data Scientist / Machine Learning Scientist

Hybrid – London( 3 days office-2 days remote )

Rate 500-550 Outside IR 35(Negotiable)

Contract 6 months initially, likely to extend

Build Production-Grade AI Systems at Scale

We’re Looking for AI Builders — Not Just Experimenters

If you’ve deployed real-world LLMs, built autonomous AI agents, and engineered scalable AI systems that people actually use, this is the opportunity to shape the future of AI across a global organisation.

We’re building next-generation AI capabilities across both:

• AI-powered SaaS / B2B products
• Enterprise-wide AI transformation initiatives

You’ll work on high-impact systems that automate workflows, enhance decision-making, and deliver measurable business value at scale.

What You’ll Build

You’ll design and deploy intelligent AI systems powered by:

• Large Language Models (LLMs)
• Agentic AI frameworks
• Retrieval-Augmented Generation (RAG)
• Multi-agent orchestration
• Tool-using autonomous workflows

This is a hands-on engineering role focused on production delivery, scalability, reliability, and business impact.

Your Work Will Include

• Building AI agents with reasoning, planning, memory, and tool orchestration
• Developing advanced RAG pipelines and context-aware AI systems
• Designing MCP-style architectures and interoperable AI workflows
• Creating recommendation, forecasting, and classification models on large-scale datasets
• Automating complex business operations using AI-driven decision systems
• Integrating AI into APIs, enterprise platforms, and customer-facing products
• Optimising latency, inference performance, observability, and cost efficiency

What We’re Looking For

We want engineers and scientists who can take AI from concept to production.

Strong Experience In

• LLMs, GenAI, and Agentic AI systems
• LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks
• RAG pipelines and vector databases
• AI agents and multi-agent orchestration
• Python, PyTorch, TensorFlow, Scikit-learn
• Cloud AI platforms such as AWS, Azure, or GCP
• Production deployment, MLOps, and scalable AI infrastructure
• API integration and workflow automation

Bonus Points For

• MCP / Model Context Protocol experience
• Fine-tuning and evaluation frameworks
• Recommendation systems and forecasting models
• Real-world enterprise AI transformation experience
• Experience balancing model quality, latency, and operational cost

Why Join US?

• Work on AI systems used at global scale
• Join a production-first AI engineering culture
• Build technology that directly impacts products, operations, and business strategy
• Collaborate with strong engineering, product, and data teams
• Influence how enterprise AI is designed and deployed across a global organisation

If you enjoy solving complex problems, deploying real AI systems, and building beyond prototypes, this role offers the opportunity to make a genuine impact.