Manager AI and Applied Research

Are you excited about working at the forefront of applied research in an industry setting? Thomson Reuters Labs in Toronto is seeking scientists with a passion for solving problems using state‑of‑the‑art information retrieval, natural language processing and generative AI, to lead a team of high performing ML scientists and research engineers.

What does Thomson Reuters Labs do? We experiment, we build, we deliver. We support the organization and our customers through applied research in informational retrieval and natural language processing. We work closely with product and domain experts to identify compelling solutions at the intersection of user need and technical feasibility. Our team is responsible for designing the next generation of tax, accounting and audit compliance software for Tax Professionals and Corporates in the US, and across the global markets.

We own AI innovation for Thomson Reuters' core tax products, including Ultra Tax, Cloud Audit Suit, Sure Prep and ONESOURCE. We work with the latest LLM prompting and agentic AI approaches to build cutting edge products.

In this opportunity as Manager, Applied Research you will:

• Manage
  :
  Direct the efforts of a team of Applied Scientists and Research Engineers, ensuring a high-performance culture. Nurture your team's career development and manage performance expectations through servant leadership and active coaching.
• Lead and Inspire
  :
  Build, mentor, and grow a high‑performing team of applied scientists.
• Drive Research to Production
  :
  Translate state‑of‑the‑art AI research into scalable, production‑ready solutions.
• Shape Strategy
  :
  Partner with Product and Engineering leaders to define and execute the AI‑driven product roadmap.
• Ensure Operational Excellence
  :
  Oversee scaling of experiment and LLMOps platforms, balancing reusability and innovation.
• Champion Innovation
  :
  Explore emerging technologies, foster experimentation, and share impact and ideas to both technical and non‑technical audiences.

You're a fit for the role of Manager, Applied Research if your background includes:

• PhD in a relevant discipline or Master's plus a comparable level of experience.
• 8+ years hands‑on experience building IR / NLP systems for commercial applications.
• Strong experience in GenAI / RAG / LLM.
• Prior management experience – coaching & developing high‑performing teams.
• Strong track record of delivering AI solutions at scale in enterprise environments.
• Ability to influence senior stakeholders and align AI initiatives with business goals.
• Experience delivering minimum viable products in a large enterprise environment.
• Demonstrable experience translating complex problems into successful AI applications.
• Experience writing production code and ensuring well‑managed software delivery.
• Expertise in several of the following areas: robust Python development, MLOps, containerization, cloud infrastructure (AWS and Azure), advanced search and recommendation technology, orchestration of ML pipelines for real‑time inference, microservices architecture, model monitoring and governance.
• Outstanding communication, problem solving, and analysis skills.

• Experience innovating state‑of‑the‑art research to solve real‑world problems.
• Experience designing and implementing solutions with large language models.
• Relevant publications at ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, KDD, or similar.
• Advanced proficiency in Python, Java, or Scala.

Eligible office location(s) for this role include one or more of the following:
Eagan, MN, Toronto, New York City. For any eligible US locations, the base compensation range for this role is $157,500 – $292,500. The base compensation range for this role in other listed locations is $181,400 – $337,000.

• Impact at Scale
  :
  Your work will power mission‑critical products used by millions worldwide.
• Innovation Culture
  :
  Autonomy to experiment with cutting‑edge AI technologies.
• Career Growth
  :
  Opportunities to lead, publish, and shape the future of AI in a global enterprise.

• Hybrid Work Model
  :
  Flexible hybrid working environment (2‑3 days a week in the office).
• Flexibility &…