Manager, Lead Research Scientist, Training Data; Foundational Research

Position: Manager, Lead Research Scientist, Training Data (Foundational Research)
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**** Foundational Research
** is the dedicated core Machine Learning research division of Thomson Reuters. 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)
* Data-centric Machine Learning (Synthetic Data, Curriculum Learning, Learned data mixtures, etc.)
* 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.)
* 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 stateof-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
** 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:
Innovate:
You will work at the very cutting edge of AI Research at an institution with some of the richest data sources in the world. Through your work, you will help us make the best use of this resource, in a dynamic flywheel that connects data collection & annotation with model training and expert evaluation, helping us continuously improve our training data.

You will also develop novel performance-driven data sub-selection methods together with the latest training insights from our researchers.
* 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 patterns 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…