Senior Director, Applied Research
Thomson ReutersRemotePosted 11 April 2026
Tech Stack
Job Description
Senior Director, Applied Research
Want to work at the forefront of applied research in an industry setting? Like the sound of a role that lets you put your research into practice and shape the future of AI-driven products? Thomson Reuters Labs might be the place for you.
Thomson Reuters Labs is seeking an experienced applied scientist with a strong product mindset to lead a high-performing team developing transformative solutions for tax, audit, and accounting professionals.
What does TR Labs do?
We experiment, we build, we deliver. We support the organization and our customers through applied research and innovation. We work closely with product and domain experts to identify compelling solutions at the intersection of customer needs and technical feasibility. We partner closely with product engineering teams to deliver real value in high-stakes settings, where accuracy and verifiability are essential.
Our team is designing the next generation of agentic AI for tax and accounting professionals around the globe. This is an opportunity to create entirely new workflows addressing fundamental challenges in the industry. Thomson Reuters has all the ingredients — from annotated tax law to robust tax engines and end-to-end solutions for data management, filing, audit, and compliance. Come join the R&D team behind Thomson Reuters' portfolio of tax products, including Checkpoint, CoCounsel Tax, and OneSource.
About the Role
This role carries significant scope to influence product strategy and shape the next generation of AI capabilities for Thomson Reuters' flagship tax products.
As a Senior Director, Applied Research , you will:
Design and develop AI features that reimagine customer workflows.
Inform business and Labs leadership on long-term AI strategy and partnerships.
Influence product strategy with high-value insights around usage, quality, and customer feedback, as well as deep technical knowledge and experience building successful AI/ML products.
Continuously improve ways of working with cross-functional teams in a fast-paced, tightly embedded R&D cycle.
Engage subject matter experts in concept development and design workshops.
Inspire a team of highly talented individuals, fostering a culture of innovation, collaboration, and continuous learning.
About You
The ideal candidate will have a strong background in AI/ML, substantial experience building language technology for commercial products, demonstrated success leading high-performing teams, and the soft skills to bridge both technical and business perspectives.
Minimum Qualifications:
PhD in Computer Science, Machine Learning, or a related field — or a Master's degree plus comparable experience.
Demonstrable, hands-on experience building AI/ML systems for commercial applications.
Demonstrable management experience, including coaching and developing high-performing teams.
Experience designing and implementing solutions with large language models.
Experience innovating state-of-the-art solutions to solve challenging real-world problems.
Outstanding communication and analytical skills.
Preferred Qualifications:
Experience building solutions for information retrieval in complex vertical domains, such as taxonomy induction, document understanding, agentic search, knowledge graphs, and/or neuro-symbolic approaches.
Experience with AI agent evaluation, language model training with verifiable rewards, and/or synthetic data generation.
Relevant publications at ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, KDD, or similar venues.
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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 ba ... (truncated, view full listing at source)
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