Data Scientist

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.