Data Marketing 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.