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Lead Applied Scientist, Search & Information Retrieval
Posted 2 weeks ago
About the role
- Lead Applied Scientist designing production search and retrieval systems for Thomson Reuters legal, tax, and accounting products. Driving ranking, semantic retrieval, evaluation, and AI strategy.
Responsibilities
- Own the design, development, and production deployment of large-scale search and information retrieval systems powering Westlaw, Practical Law, CoCounsel, and next-generation Thomson Reuters search experiences
- Design and deploy search architectures for large-scale legal, tax, and enterprise content collections
- Build and optimize ingestion pipelines that analyze, enrich, and prepare documents for retrieval
- Develop ranking and re-ranking systems using traditional information retrieval techniques and modern LLM-based approaches
- Improve retrieval quality through semantic retrieval, hybrid retrieval, query understanding, and relevance optimization
- Design evaluation frameworks for retrieval performance, relevance, ranking quality, and end-user outcomes
- Lead technical decisions around indexing strategies, retrieval architectures, ranking models, and search infrastructure
- Partner with engineering teams to deliver scalable, reliable, and performant search services
- Contribute to self-service search platform capabilities used by internal product teams
- Provide technical input to senior leadership on search, retrieval, and AI strategy
- Mentor applied scientists and machine learning practitioners across the organization
- Publish research and measure success through shipped, production-performing systems
Requirements
- PhD in Computer Science, Information Retrieval, AI, Machine Learning, NLP, or a related field preferred
- 8+ years of industry experience building production search, information retrieval, ranking, or recommendation systems
- Publications at SIGIR, ACL, EMNLP, NeurIPS, ICLR, KDD, WWW, or equivalent venues
- Strong production Python skills
- Experience with PyTorch, Hugging Face Transformers, and distributed model development
- Knowledge of search engine architecture, indexing systems, and ingestion pipelines
- Experience building ranking and re-ranking systems
- Knowledge of information retrieval, semantic retrieval, hybrid retrieval, and vector search architectures
- Knowledge of query understanding, relevance optimization, and search evaluation methodologies
- Experience with retrieval systems supporting large collections of text-rich content
- Experience with LLM-enhanced retrieval, RAG architectures, and retrieval optimization
- Experience with end-to-end measurement and evaluation of search quality and user outcomes
- Experience with legal, regulatory, tax, scientific, or other text-heavy domains preferred
- Experience building retrieval systems over large enterprise knowledge repositories preferred
- Experience with Elasticsearch, OpenSearch, Solr, Vespa, or similar search technologies preferred
- API platform development and self-service search platforms experience preferred
- Experience with agentic AI systems incorporating retrieval capabilities preferred
- Experience with AzureML or AWS SageMaker preferred
- Experience building systems combining search, retrieval, and document understanding capabilities preferred
Benefits
- Flexible work arrangements, including work from anywhere for up to 8 weeks per year
- Flexible vacation
- Two company-wide Mental Health Days off
- Headspace app access
- Retirement savings
- Tuition reimbursement
- Employee incentive programs
- Resources for mental, physical, and financial wellbeing
- Two paid volunteer days off annually
- Comprehensive health, dental, vision, disability, and life insurance programs (United States)
- 401k plan with company match (United States)
- Sick and safe paid time off
- Paid holidays
- Parental leave
- Sabbatical leave
- Flexible Spending and Health Savings Accounts
- Fitness reimbursement
- Employee Assistance Program
- Group Legal Identity Theft Protection benefit
- 529 Plan access
- Commuter benefits
- Adoption & Surrogacy Assistance
- Employee Stock Purchase Plan
- Potential eligibility for an Annual Bonus based on enterprise and individual performance
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