Senior Machine Learning Scientist
Location: UK or Poland (Remote or Hybrid)
Compensation: Dependent on experience
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 + 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)
Opportunity to share in the company’s success through options
Dog-friendly office in London 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.
Key Responsibilities
Train, evaluate and iterate on ML models and agentic systems for customer feedback, including owning 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.
Required Skills
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. 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.
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.
Technical curiosity and keen interest in AI – 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.
Preferred Add‑On Qualifications
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 verifiable reward (RLVR).
Company
Chattermill Analytics Limited
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