Lead Applied Scientist
Remote · London, England, United Kingdom
Job Summary
Lead Applied Scientist role to design and prototype AI/ML methods that improve data quality, scale human judgement, and support robust AI evaluation workflows. Collaborate with product and engineering to translate scientific methods into scalable platform capabilities, communicate trade-offs clearly, and drive practical value through prototypes, benchmarks, and experiments. Requires PhD or MSc and 3+ years of applied ML/AI experience, with strong Python skills, RLHF/LLM expertise, and experience enabling human-in-the-loop evaluation in real customer contexts.
Required Qualifications
- PhD or MSc in Computer Science, Mathematics, Statistics, Machine Learning, or a related field
- 3+ years of applied ML, AI research, or data science experience with demonstrated real-world impact
- Experience with human-in-the-loop AI systems, including RLHF, annotation pipelines, data quality modelling, judgement aggregation, benchmarks, or AI evaluation
- Fluency with modern LLM and agentic techniques, such as Retrieval-Augmented Generation (RAG), LLM-as-judge, multi-agent workflows, synthetic data generation, and automated quality review
- Strong Python skills and the ability to quickly build, test, and iterate on working prototypes
- Good judgement on when to use simple statistical methods, classical ML, LLMs, or agentic approaches
- Ability to translate ambiguous product or customer problems into clear hypotheses, experiments, metrics, and reusable methodologies
- Strong cross-functional communication and experience partnering with product and engineering teams
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