Data Scientist / Machine Learning Scientist
Hybrid – London( 3 days office-2 days remote )
Rate 500-550 Outside IR 35
Contract 6 months initially
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.