Applied Scientist
Hybrid · London, England, United Kingdom or Zug, Zug, Switzerland
Job Summary
Applied Scientist role at Thomson Reuters Labs focusing on developing and implementing ML/AI solutions across legal, tax, and regulatory domains. Responsibilities include designing experiments, building models, translating research into production-ready features, and collaborating with product/engineering teams to deliver measurable customer impact. Required to have advanced degrees in CS/ML with hands-on experience in information retrieval, NLP, ML, or generative AI; strong Python and ML framework skills; cloud familiarity; experience with LLMs, RAG, and agentic frameworks; and a track record of publications. The role supports a hybrid work model with 2-3 days in the office and flexible remote options (up to 8 weeks work-from-anywhere per year).
Required Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning or a related field
- 1-2 years hands-on experience building systems using modern techniques in information retrieval, NLP, machine learning, or generative AI (e.g., deep learning, transformer architectures, hybrid search, dense retrieval, vector databases, or agentic systems)
- Strong programming skills in Python and familiarity with a modern ML framework (PyTorch, JAX, DeepSpeed, or similar)
- Experience with cloud development environments (AWS, Azure, or GCP)
- Experience implementing and evaluating solutions with large language models and LLM evaluation frameworks (e.g., OpenAI Evals, HELM, LM Harness, or custom tools)
- Experience with retrieval-augmented generation (RAG), tool-using agents, and agentic frameworks
- Publications or preprints in NeurIPS, ACL, EMNLP, ICLR, SIGIR
- Experience with production code and MLOps practices
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