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

Are you a curious and open-minded individual with an interest in conducting state-of-the-art foundational machine learning research? Thomson Reuters Labs is seeking Research Scientists with a passion for building complex agent-based AI systems in a data-rich, complex academic environment driven by real-world problems.

Foundational Research

We are focused on research and development, with a particular focus on advanced algorithms and training techniques for Large Language Models (LLMs). We are building a strong foundation of research capabilities across different areas and are looking for managers who can inspire and guide their teams, are willing to roll up their sleeves and participate in designing, coding, conducting experiments, and translating findings into concrete deliverables. Our focus areas are:

• LLM Training (Continued Pretraining, Instruction Tuning, Reinforcement Learning Alignment, Distributed Training, Efficient ML techniques)
• Post-training techniques for planning, reasoning & complex workflows (e.g., Reasoning Models, LLMs + Knowledge Graphs, Test time compute, CoT pipelines, Tool use & API calling, etc.)
• Data-centric Machine Learning (Synthetic Data, Curriculum Learning, Learned data mixtures, etc.)
• Evaluation (Benchmarks, Human-in-the-loop, red teaming/Adversarial Testing, Hallucination detection, ...)

We work collaboratively both with TR Labs (TR’s applied research division), academic partners at world-leading research institutions and subject matter experts with decades of experience. We experiment, prototype, test, and deliver ideas in the pursuit of smarter and more valuable models trained on an unprecedented wealth of data and powered by state-of-the-art technical infrastructure. Through our unique institutional experience, we have access to an unprecedented number of subject matter experts involved in data collection, testing and evaluation of trained models.

As a Research Scientist Manager, you will play a key part in leading a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company’s leading internal AI model development. You will have the opportunity to publish your research findings as well as contribute to our proprietary AI model research & development. Thomson Reuters Labs is known for consistently delivering successful data-driven ML solutions in pursuit of academic excellence and support of high-growth products that serve Thomson Reuters customers in new and exciting ways.

About the role

• 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: Working 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).

About you

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

Required qualifications

• 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, tensorflow, …)
• 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.

Preferred qualifications

• 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.

You will enjoy

• 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.
• Competitive compensation & benefits packages: The opportunity to earn while learning new skills.

What’s in it For You?

• 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 office‑based roles while delivering a seamless experience that is digitally and physically connected.
• 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.
• Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real‑world solutions.
• Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company‑wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
• Culture: Globally recognized, award‑winning reputation for inclusion and belonging, flexibility, work-life balance, and more.
• Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro‑bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
• Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency.

We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them.