Overview
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 AI systems in a data-rich, complex academic environment driven by real-world problems. Foundational Research is the dedicated core Machine Learning research division of Thomson Reuters. We focus on research and development, with particular emphasis 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 datamixtures, 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 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 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.
Responsibilities
* Lead: Involvement in strategic planning, hiring and management in foundational research. Opportunity to master management skills, mentor, lead and help direct reports grow and contribute to the wider group.
* Innovate: Work at the cutting edge of AI Research with rich data sources; help maximize data utility through a dynamic workflow that connects data collection & annotation with model training and expert evaluation, and develop novel data sub-selection methods with latest training insights.
* Experiment and Develop: Participate in the entire research and model development lifecycle, brainstorming, coding, testing, and delivering high-quality reports at leading international academic conferences.
* Collaborate: Work within a collaborative global team of research engineers both within Thomson Reuters and with academic partners at world-leading universities.
* Communicate: Share technical findings with the wider community through seminars, lectures, conferences, publications, and/or technical assets (data & models).
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) with focus on training data curation, synthetic data generation, etc.
* 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 clearly, both orally and in writing.
* Curious and innovative disposition capable of devising novel, well-founded algorithmic solutions to relevant problems.
* Strong social skills and ability to motivate, inspire and mentor team members. Comfortable in fast-paced, agile environments, managing uncertainty and ambiguity. High-impact publications or equivalent influence in the research community.
* 5+ years of hands-on experience leading teams building advanced ML / NLP / AI systems in academia or industry.
* Extensive experience with deep learning and large-scale model training.
* Extensive experience working with LLM training-data, ideally by involvement in training large-scale foundation models.
* Strong software and/or infrastructure engineering skills with evidence of well-managed software delivery (code contributions to open-source libraries or production code).
* Experience training large-scale models over distributed nodes with cloud tools (e.g., Amazon AWS, MS Azure, Google Cloud).
Thomson Reuters informs the way forward by bringing together trusted content and technology to help professionals make informed decisions. Reuters, part of Thomson Reuters, is a world-leading provider of trusted journalism and news. As a global business, we value diverse backgrounds, perspectives, and experiences. We are an Equal Employment Opportunity Employer, provide a drug-free workplace, and make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here.
Benefits & Perks
* Learning and development: On-the-job coaching and learning with cutting-edge methods and technologies.
* Plenty of data, compute, and high-impact problems: Access to large datasets and thoughtful infrastructure support.
* Competitive compensation & benefits: Hybrid work model (2-3 days in the office, depending on role).
* Flexibility & Work-Life Balance: Flexible work arrangements, including work from anywhere for up to 8 weeks per year.
* Career Development: Growth-focused culture and tools to grow and lead in an AI-enabled future.
* Industry Benefits: Comprehensive plans including vacation, mental health days, Headspace, retirement, tuition reimbursement, and wellbeing resources.
* Culture & Social Impact: Inclusive culture with opportunities for volunteering and ESG initiatives.
* Real-World Impact: Contribute to delivering trusted information and supporting professionals globally.
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