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

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

Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead cutting-edge research in AI and machine learning, guiding a diverse global team.
  • Company: Join Thomson Reuters Labs, a leader in innovative AI solutions.
  • Benefits: Enjoy competitive pay, flexible work options, and comprehensive wellness programs.
  • Other info: Collaborate with top experts and access vast datasets for groundbreaking research.
  • Why this job: Make a real-world impact while pushing the boundaries of AI technology.
  • Qualifications: PhD and 3+ years leading ML/NLP teams; strong publication record required.

The predicted salary is between 80000 - 100000 £ per year.

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.

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.
  • 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.

Manager, Lead Research Scientist, LLM Agents (Foundational Research) employer: PowerToFly

Thomson Reuters Labs is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the field of foundational machine learning research. With access to vast datasets and cutting-edge technology, employees are empowered to tackle real-world challenges while enjoying a flexible hybrid work model, comprehensive benefits, and ample opportunities for professional growth and development. Join a globally recognized team dedicated to making a meaningful impact in the pursuit of justice, truth, and transparency.

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Contact Details:

PowerToFly Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Manager, Lead Research Scientist, LLM Agents (Foundational Research)

Tip Number 1

Network like a pro! Reach out to your connections in the industry, attend relevant conferences, and engage with professionals on platforms like LinkedIn. We can’t stress enough how important it is to build relationships that could lead to job opportunities.

Tip Number 2

Prepare for interviews by researching the company and its projects. Understand their focus areas, especially in foundational machine learning research. We recommend practising common interview questions and even some technical challenges related to LLMs to show you’re ready to roll up your sleeves!

Tip Number 3

Showcase your passion for innovation! During interviews, share your ideas on cutting-edge AI approaches or recent advancements in ML. We love candidates who can think outside the box and contribute to solving real-world challenges.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for curious minds who are eager to contribute to our mission of delivering smarter AI solutions.

We think you need these skills to ace Manager, Lead Research Scientist, LLM Agents (Foundational Research)

Machine Learning Research
Natural Language Processing (NLP)
Large Language Models (LLMs)
Deep Learning Frameworks (e.g., PyTorch, TensorFlow, JAX)
Agent-based AI Systems
Algorithm Development
Data-centric Machine Learning

Some tips for your application 🫡

Show Your Passion:When writing your application, let your enthusiasm for foundational machine learning research shine through. We want to see your curiosity and how it drives your work in AI systems.

Tailor Your CV:Make sure your CV highlights relevant experience in ML/NLP/AI systems. We’re looking for specific projects or roles that showcase your leadership and technical skills, so don’t hold back!

Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share your vision for leading research teams and how you plan to innovate in agent-based AI systems.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!

How to prepare for a job interview at PowerToFly

Know Your Research

Dive deep into the latest advancements in foundational machine learning and LLMs. Be prepared to discuss your own research and how it aligns with the company's focus areas, like agent-based AI systems and data-centric machine learning.

Showcase Your Leadership Skills

As a potential manager, highlight your experience in leading teams and mentoring others. Share specific examples of how you've inspired your team to innovate and tackle complex problems in a collaborative environment.

Prepare for Technical Questions

Brush up on your knowledge of deep learning frameworks and advanced algorithms. Expect questions that test your understanding of LLM training techniques and evaluation methods, so be ready to discuss your hands-on experience.

Communicate Clearly

Practice articulating your research findings and technical concepts in a clear and engaging manner. Remember, effective communication is key, especially when discussing complex ideas with both technical and non-technical audiences.