Senior 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, PracticalLaw, 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.

About You

You hold a PhD or Master's in Computer Science, AI, NLP, or a related field, with 5+ 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.

What You'll Do

• 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 optimization
• 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

Required Qualifications

• PhD or Master's in Computer Science, AI, NLP, or a related field
• 5+ 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, DeepSpeed, Torchtune, or LlamaFactory
• Hands-on Production Depth Required In:
  • 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

Preferred Qualifications

• 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
• AzureML or AWS SageMaker

Benefits

• Flexibility & Work-Life Balance: Flex My Way supportive workplace policies, including work from anywhere for up to 8 weeks per year
• Career Development and Growth: Grow My Way programming and skills-first approach for continuous learning and skill development
• Industry Competitive Benefits: Flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing
• Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and values: Obsess over our Customers, Compete to Win, Challenge (Y)our 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
• Making a Real-World Impact: Help customers pursue justice, truth, and transparency across legal, tax, accounting, compliance, government, and media

Pay

• United States: $137,100 USD - $254,700 USD base compensation range
• Ontario, Canada: $100,000 CAD - $145,000 CAD base compensation range
• Positioned within range based on knowledge, skills, and experience with consideration for internal equity
• May also be eligible for an Annual Bonus based on enterprise and individual performance