Job description

Lead Applied Scientist, Search & Information Retrieval Job Description: This role sits within the applied science function. You will own the design, development, and production deployment of large-scale search and information retrieval systems that power Westlaw, Practical Law, CoCounsel, and next-generation Thomson Reuters search experiences. The problems are real, the scale is large, and the expectation is shipped, reliable, measurable impact. You will work across retrieval architectures, indexing pipelines, ranking and re-ranking systems, semantic retrieval, hybrid search, and retrieval optimization for complex legal, tax, and accounting content. Multiple product teams depend on what this function delivers. Key Responsibilities: You hold a PhD in Computer Science, Information Retrieval, Machine Learning, NLP, or a related field, with 8 years of post-degree industry experience building and deploying search and retrieval systems at scale. You have hands-on depth across indexing, retrieval, ranking, relevance evaluation, and production deployment. You publish, you mentor, and you measure success by what ships and performs in production. You understand search beyond simply consuming vector databases or retrieval APIs. You have built, optimized, and evaluated search systems that solve real user problems. Design and deploy search architectures supporting 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 both traditional IR 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 the development of 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 Required Qualifications: 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 and experience with PyTorch, Hugging Face Transformers, and distributed model development Search engine architecture, indexing systems, and ingestion pipelines Ranking and re-ranking systems rather than solely consuming search technologies Information retrieval, semantic retrieval, hybrid retrieval, and vector search architectures Query understanding, relevance optimization, and search evaluation methodologies Retrieval systems supporting large collections of text-rich content LLM-enhanced retrieval, RAG architectures, and retrieval optimization End-to-end measurement and evaluation of search quality and user outcomes Preferred Qualifications: Experience with legal, regulatory, tax, scientific, or other text-heavy domains Building retrieval systems over large enterprise knowledge repositories Experience with Elasticsearch, OpenSearch, Solr, Vespa, or similar search technologies API platform development and self-service search platforms Agentic AI systems that incorporate retrieval capabilities AzureML or AWS SageMaker Experience building systems that combine search, retrieval, and document understanding capabilities #LI-SM2 This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization. What’s in it For You? Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits: We offer comprehensive benefit plans to include 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 more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real-World Impact:   We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. Our use of AI within the recruitment process Thomson Reuters utilizes Artificial Intelligence (AI) to support parts of our global recruitment process. Unless you opt-out, our AI system will assess the information provided by you and compare it to the requirements listed for the role, and present the result to our recruitment personnel for further review. The AI system acts as a supporting tool, but there is always a human making the decision if you will be considered for the role. In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: 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; Tuition Reimbursement; and access to Employee Stock Purchase Plan. Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations. For any eligible US locations, unless otherwise noted, the base compensation range for this role is $147,600 USD - $274,200 USD. For Ontario, Canada, the base compensation range for this role is $140,000 CAD - $175,000 CAD. Base pay is positioned within the range based on several factors including an individual’s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs. This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance. This job posting will close 03/31/2027. About Us Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here. Learn more on how to protect yourself from fraudulent job postings here. More information about Thomson Reuters can be found on thomsonreuters.com

Requirements

Must-haves

Lead Applied Scientist, Search & Information Retrieval
Design and deploy search architectures supporting 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 both traditional IR 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 the development of 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
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 and experience with PyTorch, Hugging Face Transformers, and distributed model development
Search engine architecture, indexing systems, and ingestion pipelines
Ranking and re-ranking systems rather than solely consuming search technologies
Information retrieval, semantic retrieval, hybrid retrieval, and vector search architectures
Query understanding, relevance optimization, and search evaluation methodologies
Retrieval systems supporting large collections of text-rich content
LLM-enhanced retrieval, RAG architectures, and retrieval optimization
End-to-end measurement and evaluation of search quality and user outcomes
Building retrieval systems over large enterprise knowledge repositories

Nice-to-haves

Required Qualifications: PhD in Computer Science, Information Retrieval, AI, Machine Learning, NLP, or a related field preferred
Preferred Qualifications: Experience with legal, regulatory, tax, scientific, or other text-heavy domains

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningllmaipythonapiaws

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off

Parental Leave