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Thomson Reuters Labs is seeking a Director, Applied Research to lead a high-performing team developing agentic AI for tax and accounting professionals. You will shape AI capabilities for transformative workflows at scale, partnering with product and domain experts to deliver real value in demanding environments.
The role requires a PhD or equivalent depth, 10+ years in AI/ML with hands-on production experience, and 5+ years leading teams.
Are you excited about working at the forefront of applied research in an industry setting? Thomson Reuters Labs is seekingan experiencedscientist withstrongproduct mindset toleada high-performing team developing transformativesolutions for tax, audit, and accounting professionals
What doesTR Labsdo? We experiment, we build, we deliver. We support the organization and our customers through applied researchandinnovation. We work closely with product and domain experts toidentifycompelling solutions at the intersection ofcustomerneedsand technical feasibility.We partner closely with product engineering teams to deliverreal value in high-stakes settings,where accuracy and verificationare essential
Our team is designingthe nextgenerationofagentic AIfortax & accounting professionalsaround the globe.Thisisanopportunityto create entirely new workflows addressing fundamental challenges in the industry.TR has all the ingredientsfromannotatedtax lawtorobusttaxengines andend-to-end solutions for data management, filing, audit, and compliance.Comejoin the R&Dteamfor Thomson Reuters’portfolio oftaxproducts, including Checkpoint,CoCounselTax,and OneSource
You hold a PhD in Computer Science, Machine Learning, or a closely related field or a Master's with equivalent depth, a strong science background, and a relevant publication record. You bring 10+ years of hands-on industry experience building AI/ML systems for commercial applications, with recent direct experience developing LLM-based and agentic systems in production. You have 5+ years leading and developing high-performing applied science or ML teams