Senior Machine Learning Scientist

Job description

Senior Machine Learning Scientist 🌍 UK or Poland (Remote or Hybrid, it’s up to you!) 💰 Dependent on experience 📈 Be part of our success with the opportunity to join our company equity scheme Our Perks ❤️ Monthly Health & Wellness budget, increasing with length of service 📚 Annual Learning and Development budget, increasing with length of service 🤸🏽‍♂️ Flexible working in a choice-first environment - we trust the way you want to work! 🖥️ Work From Home Allowance 🌴 25 Holiday Days + your local bank holidays, plus an extra day for every year of service 🎂 Your birthday off 🍼 Enhanced Family Leave (UK Only), Fertility Leave, and Neonatal Leave ⚕️ Optional Healthcare Plan 🛟 Life & income protection (Location dependent) 🤝 Employee Assistance Programme (UK Only) 📈 The opportunity to share in the company’s success through options 🌆 If you’re in London, a dog-friendly office with great classes, events, and a rooftop terrace 🦸‍♀️ The Role 🦸‍♀️ Our mission is to help large successful brands like Uber, Amazon, Wise, HelloFresh (and more!) put their customers at the centre of everything they do. Using best-in-class tech in a fast-developing AI space, our Customer Experience Intelligence platform continuously analyses explicit and implicit feedback to enable our clients to identify what they should do next. We're hiring a Senior Machine Learning Scientist to join the team and help build and ship the next generation of that stack. 👉 What you'll be doing: Unlike many companies, we use our own custom models, specialised for customer feedback, across various parts of the stack: extraction, retrieval, reranking, summarisation, and sentiment analysis. We are also pragmatic and understand that the right solution can be a combination of off-the-shelf LLMs, bespoke fine-tuned models, and sometimes techniques that utilise no LLM at all. This means you will: Train, evaluate, and iterate on ML models and agentic systems for customer feedback, including owning our custom fine-tuning pipelines. Run experiments end-to-end, track results rigorously, and make clear recommendations on what to ship, iterate, or retire. Build and maintain LLM-powered features: retrieval pipelines, reranking systems, insight agents, data mining agents, and automated taxonomy generation. Design and run robust evaluation frameworks: build test sets, define metrics, evaluate non-deterministic sy…