At a Glance
- Tasks: Join us to develop cutting-edge ML models for customer feedback analysis.
- Company: Dynamic tech company focused on AI and customer experience.
- Benefits: Flexible working, competitive salary, equity scheme, and wellness budget.
- Other info: Diverse and inclusive team culture, with excellent growth opportunities.
- Why this job: Make a real impact in AI while working with top brands like Uber and Amazon.
- Qualifications: Deep knowledge of ML, strong PyTorch skills, and experience with real-world data.
The predicted salary is between 60000 - 80000 £ per year.
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.
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!
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.
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 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.
- 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.
It would be a bonus if you:
- 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).
Diversity & Inclusion
We want to enable exceptional experiences for everyone, and to achieve this we need everyone’s voice in our team. We are on a mission to bring more diversity into the business and to give everyone (from all backgrounds and abilities) a chance to join us, even if they may not fit all of the requirements set out in this job spec. We realise that some may be hesitant to apply for a role when they don’t meet 100% of the listed requirements – we believe in potential and will happily consider all applications based on the skills and experience you have, we’d love to be part of your growth and we encourage you to apply!
Senior Machine Learning Scientist in London employer: Chattermill
Join a forward-thinking company that prioritises employee well-being and growth, offering flexible working arrangements and a generous benefits package including an annual learning budget and health & wellness support. With a commitment to diversity and inclusion, we foster a collaborative culture where your contributions are valued, and you can thrive in a dynamic environment focused on cutting-edge AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your projects. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 3
Showcase your passion for AI and machine learning! During interviews, share your experiences and insights about recent advancements in the field. This will demonstrate your enthusiasm and technical curiosity.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Senior Machine Learning Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Machine Learning Scientist role. Highlight your expertise in transformer architectures and PyTorch, and don’t forget to mention any relevant projects you've worked on!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for our team. Be sure to connect your experiences with what we’re looking for in the job description.
Show Off Your Projects:If you’ve got any personal or professional projects that showcase your machine learning skills, include them! We love seeing practical applications of your work, especially if they relate to customer feedback or AI solutions.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining the StudySmarter family!
How to prepare for a job interview at Chattermill
✨Know Your Stuff
Make sure you brush up on transformer architectures and PyTorch. Be ready to discuss your experience with custom training loops and fine-tuning techniques like LoRA. The more specific examples you can provide, the better!
✨Show Your Problem-Solving Skills
Prepare to talk about how you've tackled messy real-world text data in the past. Think of a few scenarios where you identified problems and drove solutions forward. This will show your initiative and ownership.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You might be asked to translate your work for non-technical audiences, so being able to communicate effectively is key. Try explaining your projects to a friend who isn’t in tech!
✨Be Curious and Engaged
Demonstrate your passion for AI and machine learning. Share any recent experiments or projects you've been involved in, and don’t hesitate to ask insightful questions about the company’s tech stack and future directions during the interview.