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Director, Applied Research

Job in New York, New York County, New York, 10261, USA
Listing for: Refinitiv
Full Time position
Listed on 2026-08-08
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 280000 USD Yearly USD 180000.00 280000.00 YEAR
Job Description & How to Apply Below
Location: New York

Director, Applied Research

Are you excited about working at the forefront of applied research in an industry setting? Thomson Reuters Labs is seeking an experienced scientist with strong product mindset to lead a high-performing team developing transformative solutions for tax, audit, and accounting professionals.

About the role

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 verification are essential.

Our team is designing the next generation of agentic AI for tax & accounting professionals around the globe. This is an opportunity to create entirely new workflows addressing fundamental challenges in the industry. TR 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 for Thomson Reuters' portfolio of tax products, including Checkpoint, CoCounsel Tax, and One Source.

About You

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.

What

You’ll Do
  • Lead and develop a high-performing applied science team working on agentic AI for tax and accounting professionals
  • Drive the design and delivery of AI features that meaningfully reimagine customer workflows in high-stakes, accuracy-critical settings
  • Serve as a strategic thought partner to Labs leadership, product leadership, and key business stakeholders on long-term AI strategy, partnerships, and capability roadmap
  • Influence product strategy through deep technical knowledge combined with insight from usage data, quality metrics, and customer feedback
  • Continuously improve ways of working across R&D and product engineering in a fast-paced, tightly embedded delivery cycle
  • Engage domain and subject-matter experts in concept development and design workshops
  • Foster a team culture of innovation, rigour, collaboration, and continuous learning
Required Qualifications
  • PhD in Computer Science, Machine Learning, or a related field or Master's with a strong science background and relevant publication record — required
  • 10+ years of hands-on industry experience building AI/ML systems for commercial applications — not research-only experience
  • Recent, direct hands-on experience developing LLM-based and agentic AI systems for production, non-trivial use cases
  • 5+ years of experience managing and developing high-performing applied science or ML teams
  • Demonstrated success in product-oriented or customer-facing roles, with business and customer impact as the primary measure of success
  • Technical depth in AI/ML sufficient to provide effective challenge, expand on team ideas, and support high-quality technical decision-making
Preferred Qualifications
  • Technical depth in information retrieval and NLP, with experience in complex vertical domains — taxonomy induction, document understanding, agentic search, knowledge graphs, or neuro-symbolic approaches
  • Experience with AI agent evaluation, language model training with verifiable rewards, and synthetic data generation
  • Publications at ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, KDD, or equivalent
  • Experience building AI solutions for tax, legal, audit, or accounting domains
  • Track record of growth at top-tier technology companies or high-growth startups #LI-LP2
What's in it For You?

Flexibility & Work-Life Balance:
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