Lead Applied Scientist, Search & Information Retrieval
AI in this role
Lead Applied Scientist, Search & Information Retrieval
About the Role
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.
About You
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
- 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
- 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.
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.
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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
How we rate this
Lead Applied Scientist, Search & Information Retrieval at Thomson Reuters rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What are the limits of Hugging Face that you've run into, and how did you work around them?
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used Sagemaker in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, NLP, Hugging Face, PyTorch, and Sagemaker. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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