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 Data 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.
- 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 systems, handle class imbalance, and automate checkpoint comparisons.
- Improve and extend semantic search and retrieval, evolving from embedding-based approaches toward more advanced methods.
- Write production-quality code and collaborate closely with Engineering on productionisation, model serving, data pipelines, and monitoring.
- Work with Product and Commercial teams to translate business needs into practical ML solutions, and support client evaluations and accuracy benchmarking.
- Mentor team members, review code and research, and bring relevant advances from the literature into the product.
What you’ll need
- A deep working knowledge of transformer architectures.
- Strong PyTorch skills, with the ability to write custom training loops, modify model architectures, and debug issues at the tensor level. Ideally, experience with parameter-efficient fine-tuning techniques such as LoRA.
- Extensive experience working with large-scale, messy real-world text data, including classification, extraction, embeddings, re-rankers, clustering, and search.
- Experience in instruction fine-tuning and serving language models, familiarity with frameworks such as vLLM, DeepSpeed, or similar tools.
- A solid grounding in classical ML and statistics, and the judgement to choose simpler methods when they’re the right solution.
- Practical experience building with GenAI and agentic patterns.
- Excellent communication skills and confidence translating complex technical concepts for non-technical audiences (and vice versa!).
- Technical curiosity and a keen interest in AI – a love of experimenting to make the most of available technology.
- High ownership and initiative, with the ability to identify problems, prioritise effectively, and drive solutions forward.
Bonus Skills
- MSc/PhD in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Computational Linguistics or a closely related STEM field.
- Experience with reinforcement learning techniques, such as with verifiable reward (RLVR).