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 to build complex agent‑based AI systems in a data‑rich, complex academic environment driven by real‑world problems.
Focus Areas
- 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)
- Data‑centric Machine Learning (Synthetic Data, Curriculum Learning, Learned data‑mixtures)
- Evaluation (Benchmarks, Human‑in‑the‑loop, Red teaming/Adversarial Testing, Hallucination detection)
About The Role
As a Research Scientist Manager you will lead a diverse global team of experts, drive internal AI model development, and contribute to our proprietary AI model research & development. You will have the opportunity to publish research findings and contribute to the broader community.
About You
You’re a fit for the role if your background includes:
Responsibilities
- Lead strategic planning, hiring, and management of foundational research teams.
- Innovate and create new state‑of‑the‑art Agent AI/LLM Agent approaches at the cutting edge of AI research.
- Engage in the entire research & model development lifecycle: brainstorming, coding, testing, and delivering high‑quality reports at international academic conferences.
- Collaborate on a global research engineering team within Thomson Reuters and academic partners.
- Communicate technical findings through seminars, lectures, conferences, publications, and technical assets.
Required Qualifications
- PhD in a relevant discipline.
- 3+ years of hands‑on experience leading teams building advanced ML/NLP/AI systems in academia or industry.
- Strong publication record in top‑tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) with a focus on agent systems, tool use, or multi‑agent coordination.
- Familiarity with 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 for reporting and presenting research findings.
- Curious and innovative disposition capable of devising novel, well‑founded algorithmic solutions.
- Good social skills and ability to motivate, inspire, and mentor team members.
- Comfortable 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 or 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.
- Strong software and/or infrastructure engineering skills, with code contributions to open‑source libraries or production code.
- Experience training large‑scale models over distributed nodes with cloud tools such as Amazon AWS, MS Azure, or Google Cloud.
Benefits
- Learning and development opportunities through on‑the‑job coaching and cutting‑edge methods.
- Access to large datasets, compute, and high‑impact problems.
- Competitive compensation & benefits packages.
- Hybrid work model with flexible remote options.
- Work‑life balance initiatives, including flexible work arrangements and paid volunteer days.
- Comprehensive benefits: flexible vacation, mental health days, Headspace app, retirement savings, tuition reimbursement, and employee incentive programs.
- Inclusive culture with a global reputation for inclusion and belonging.
Equal Employment Opportunity
Thomson Reuters is an Equal Employment Opportunity Employer. We consider qualified employees regardless of race, color, sex/gender, pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizenship status, veteran status, or any other protected classification under applicable law. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law.
Application Disclaimer
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