Applied Scientist, Search & Information Retrieval

Applied Scientist, Search & Information Retrieval About the Role

This is an applied science position focused on building and deploying production‑grade search systems that power Westlaw, Practical Law, and CoCounsel. You will work across neural information retrieval, semantic and hybrid search, re‑ranking, and query understanding — delivering search quality and relevance at scale for legal and professional content.

You hold a PhD or Master's in Computer Science, AI, NLP, or a related field, with 3+ years of post‑degree industry experience shipping search or retrieval systems into production. You have hands‑on depth in neural IR and deep learning for NLP, you work independently, and you measure success by what performs in production.

• Design, build, and deploy end‑to‑end neural search systems including dense retrieval, hybrid search, semantic chunking, embedding models, cross‑encoders, SLM re‑rankers, and transformer‑based approaches
• Develop models for query understanding, document re‑ranking, and retrieval quality optimisation
• Build evaluation frameworks – component‑level and end‑to‑end – using expert annotation and synthetic data generation
• Drive independent technical decisions on retrieval architecture, indexing strategy, ranking models, and evaluation methodology
• Partner with engineering on delivery, reliability, and scale across multiple product lines
• Contribute to published research at venues such as SIGIR, ECIR, NeurIPS, ACL, EMNLP, and ICLR, and to intellectual property

• PhD or Master's in Computer Science, AI, NLP, or a related field
• 3+ years of post‑degree industry experience shipping search, retrieval, or RAG systems into production – not research‑only experience
• Publications at SIGIR, ECIR, NeurIPS, ACL, EMNLP, ICLR, or equivalent
• Production Python and experience with PyTorch, Deep Speed, Torchtune, or Llama Factory

• Neural IR fundamentals: BM25, hybrid search, dense retrieval (DPR, ColBERT), bi‑encoders, cross‑encoders, late interaction models
• Search and RAG system design: vector databases, retrieval strategies, document chunking, metadata filtering, re‑ranking, context optimisation, and orchestration
• Evaluation framework design for retrieval quality at component and system level
• Post‑training of large language models and their application to retrieval systems
• Deep learning and NLP fundamentals

• Search, QA, or RAG over large corpora and long documents, including legal or enterprise search
• Multi‑stage or agentic retrieval architectures and query understanding for complex information needs
• Legal domain applications: case law retrieval, precedent finding, document review
• Azure
  
  ML or AWS Sage Maker

• Hybrid Work Model: A flexible hybrid working environment (2‑3 days a week in the office depending on the role) for our office‑based roles while delivering a seamless digitally and physically connected experience.
• Flexibility & Work‑Life Balance:
  Flex My Way policy to manage personal and professional responsibilities, including up to 8 weeks of work from anywhere per year.
• Career Development and Growth:
  Continuous learning and skill development initiatives, Grow My Way programming, and a skills‑first approach to help you grow, lead, and thrive in an AI‑enabled future.
• Industry‑Competitive Benefits:
  Comprehensive benefits including flexible vacation, two company‑wide Mental Health Days off, Headspace app access, retirement savings, tuition reimbursement, incentive programs, and resources for mental, physical, and financial wellbeing.
• Culture: A globally recognized, award‑winning reputation for inclusion and belonging, flexibility, work‑life balance, and living by values such as Obsess over Customers, Compete to Win, Challenge Your Thinking, Act Fast / Learn Fast, and Stronger Together.
• Social Impact:
  Two paid volunteer days off annually, pro‑bono consulting projects, and ESG initiatives through the Social Impact Institute.
• Real‑World Impact:
  Helping customers pursue justice, truth, and transparency to uphold the rule of law and provide unbiased information worldwide.

Thomson Reuters is an equal opportunity employer. We provide a drug‑free workplace and reasonable accommodations for applicants with disabilities and sincerely held religious beliefs. We do not discriminate on the basis of race, color, sex, gender identity, marital status, veteran status, or any other protected classification under applicable law.