Senior Applied Scientist, Search & Information Retrieval

Thomson Reuters • Toronto, ON

2d • $137,100 - $254,700 • Remote

About The Position

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.

Requirements

• 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
• Hands-on production depth required in: Search and RAG system design: vector databases, retrieval strategies, document chunking, metadata filtering, re-ranking, context optimisation, and orchestration
• Hands-on production depth required in: Evaluation framework design for retrieval quality at component and system level
• Hands-on production depth required in: Post-training of large language models and their application to retrieval systems
• Hands-on production depth required in: Deep learning and NLP fundamentals

Nice To Haves

• 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

Responsibilities

• 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

Benefits

• Flexible vacation
• Two company-wide Mental Health Days off
• Access to the Headspace app
• Retirement savings
• Tuition reimbursement
• Employee incentive programs
• Resources for mental, physical, and financial wellbeing
• Market competitive health, dental, vision, disability, and life insurance programs
• Competitive 401k plan with company match
• Competitive vacation, sick and safe paid time off
• Paid holidays
• Parental leave
• Sabbatical leave
• Optional hospital, accident and sickness insurance paid 100% by the employee
• Optional life and AD&D insurance paid 100% by the employee
• Flexible Spending and Health Savings Accounts
• Fitness reimbursement
• Access to Employee Assistance Program
• Group Legal Identity Theft Protection benefit paid 100% by employee
• Access to 529 Plan
• Commuter benefits
• Adoption & Surrogacy Assistance
• Employee Stock Purchase Plan

What This Job Offers

• Job Type: Full-time
• Career Level: Senior