Manager, Lead Research Scientist, LLM Agents; Foundational Research

Manager, Lead Research Scientist, LLM Agents (Foundational Research)

Join Thomson Reuters to apply for the Manager, Lead Research Scientist, LLM Agents (Foundational Research) role in our Labs.

In this opportunity, as Research Scientist Manager you will:

• Lead:
  You will be involved in strategic planning, hiring and the management in foundational research. This gives you the opportunity to master your management skills, mentor, lead and help direct reports grow and contribute to the wider group.
• Innovate:
  You will innovate and create new state‑of‑the‑art Agent AI/LLM Agent approaches at the cutting edge of AI research. You will contribute ideas and work on solving real‑world challenges using a wealth of data in agentic contexts.
• Experiment and Develop:
  You are involved in the entire research & model development lifecycle, brainstorming, coding, testing, and delivering high‑quality reports at leading international academic conferences.
• Collaborate:
  Work on a collaborative global team of research engineers both within Thomson Reuters and our academic partners at world‑leading universities.
• Communicate:
  Actively engage in sharing our technical findings with the wider community through contributions to seminars, lectures, conferences and/or the sharing of publications and/or technical assets (data & models).

You're a fit for the role if your background includes:

• PhD in a relevant discipline.
• 3+ years of hands‑on experience leading teams building advanced ML / NLP / AI systems in academia (e.g. through student supervision) or industry.
• Strong publication record in top‑tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICLR) with specific focus on agent systems, tool use, or multi‑agent coordination.
• Familiarity with one or more deep‑learning frameworks (e.g. PyTorch, JAX, Tensor Flow).
• Experience in ML Research beyond completing a PhD (e.g., supervision, industry experience, leading academic initiatives).
• Excellent communication skills to report and present research findings and developments clearly, both orally and in writing.
• Curious and innovative disposition capable of devising novel, well‑founded algorithmic solutions to relevant problems.
• Good social skills and ability to motivate, inspire and mentor team members.
• Comfortable in working in fast‑paced, agile environments, managing uncertainty and ambiguity.

• High‑impact publications in top‑tier conferences or other influence in the research community.
• 5+ years of hands‑on experience leading teams building advanced ML / NLP / IR systems in academia (e.g. through student supervision) or for commercial applications.
• Extensive experience with deep learning and large‑scale model training.
• Extensive experience working on agent‑based systems, tool‑using AI, or multi‑agent coordination in LLM contexts (e.g., startup, industry, or extensive open‑source experience).
• Strong software and/or infrastructure engineering skills and ensuring well‑managed software delivery, as evidenced by code contributions to popular open‑source libraries or writing production code.
• Experience training large‑scale models over distributed nodes with cloud tools such as Amazon AWS, MS Azure, or Google Cloud.

• Learning and development:
  On‑the‑job coaching and learning as well as the opportunity to work with cutting‑edge methods and technologies.
• Plenty of data, compute, and high‑impact problems:
  Our scientists and engineers get to explore large datasets and discover new capabilities and insights. Thomson Reuters is best known for the globally respected Reuters News agency, but our company is also the leading source of information for legal, corporate, and tax & accounting professionals. We have over 60,000 TBs worth of legal, regulatory, news, and tax data. We also provide access to all major cloud computing platforms to our researchers and engineers.
• Competitive compensation & benefits packages:
  The opportunity to earn while learning new skills.

• Hybrid Work Model:
  We’ve adopted a flexible hybrid working environment (2–3 days a week in the office depending on the role) for our…