Manager, Lead Research Scientist, Training Data (Foundational Research)
Manager, Lead Research Scientist, Training Data (Foundational Research)

Manager, Lead Research Scientist, Training Data (Foundational Research)

Full-Time 43200 - 72000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead a global team in cutting-edge AI research and model development.
  • Company: Join Thomson Reuters Labs, a leader in foundational machine learning research.
  • Benefits: Enjoy competitive pay, flexible work options, and extensive learning opportunities.
  • Why this job: Make a real-world impact with advanced AI systems and rich data resources.
  • Qualifications: PhD required; 3+ years leading ML/NLP teams and strong publication record.
  • Other info: Collaborative culture with a focus on innovation and social impact.

The predicted salary is between 43200 - 72000 ÂŁ per year.

Manager, Lead Research Scientist, Training Data (Foundational Research)

4 days ago – Be among the first 25 applicants

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

Our Dedicated Core Machine Learning Research Division focuses on advanced algorithms and training techniques for large language models (LLMs). We build a strong foundation of research capabilities across different areas and are looking for managers who can inspire and guide their teams, participate in designing, coding, testing, and translating findings into concrete deliverables. Our focus areas include:

  • LLM Training (continued pre‑training, 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, chain‑of‑thought pipelines, tool use & API calling, etc.)
  • Evaluation (benchmarks, human‑in‑the‑loop, red‑team/ adversarial testing, hallucination detection, etc.)

We collaborate with Thomson Reuters Labs, academic partners at world‑leading research institutions, and subject‑matter experts. We experiment, prototype, test, and deliver ideas to build smarter, more valuable models trained on an unprecedented wealth of data and powered by state‑of‑the‑art technical infrastructure.

About The Role

In this opportunity, as Research Scientist Manager you will:

  • Lead: Involved in strategic planning, hiring, and management of foundational research. 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 collection, annotation, model training, and evaluation to continuously improve training data. Develop novel performance‑driven data sub‑selection methods with latest training insights.
  • Experiment and Develop: Involved in the entire research & model development lifecycle—brainstorming, coding, testing, and delivering high‑quality reports at leading international academic conferences.
  • Collaborate: Work on a collaborative global team of research engineers within Thomson Reuters and across world‑leading universities.
  • Communicate: Actively share technical findings with the wider community through seminars, lectures, conferences, and publications.

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 or industry.
  • Strong publication record in top‑tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) focusing on training data curation, synthetic data generation, etc.
  • Familiarity with deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
  • Experience in ML research beyond completing a PhD.
  • Excellent communication skills for reporting and presenting research findings clearly, orally and in writing.
  • 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 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/AI systems in academia or industry.
  • Extensive experience with deep learning and large‑scale model training.
  • Experience with LLM training data, ideally by involvement in training large‑scale foundation models.
  • Strong software and/or infrastructure engineering skills, demonstrated by code contributions to popular open‑source libraries or production code.
  • Experience training large‑scale models over distributed nodes with cloud tools such as AWS, Azure, or GCP.

You Will Enjoy

  • Learning and development: On‑the‑job coaching and learning opportunities with cutting‑edge methods and technologies.
  • Plenty of data, compute, and high‑impact problems: 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: Flexible hybrid working environment (2‑3 days a week in the office depending on the role) while delivering a seamless digitally and physically connected experience.
  • Flexibility & Work‑Life Balance: Flexible work arrangements, work from anywhere for up to 8 weeks per year, and supportive policies (Flex My Way) to manage personal and professional responsibilities.
  • Career Development and Growth: Culture of continuous learning and skill development, Grow My Way programming, and skills‑first approach for growth, leadership, and AI‑enabled future.
  • Industry Competitive Benefits: Flexible vacation, two company‑wide mental health days off, access to Headspace, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
  • Culture: Globally recognized award‑winning reputation for inclusion, belonging, flexibility, work‑life balance, and strong values (Obsess over our Customers, Compete to Win, Challenge Your Thinking, Act Fast / Learn Fast, Stronger Together).
  • Social Impact: Two paid volunteer days off annually, pro‑bono consulting projects, and ESG initiatives.
  • Making a Real‑World Impact: Help customers pursue justice, truth, and transparency by supporting the rule of law, catching bad actors, and providing trusted, unbiased information worldwide.

About Us

Thomson Reuters informs the way forward by bringing together trusted content and technology. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine specialized software and insights to empower data‑driven decision making.

We are powered by the talents of 26,000 employees across more than 70 countries. We consider it our duty to pursue objectivity, accuracy, fairness, and transparency.

Thriving on diversity and inclusion, we seek qualified employees regardless of race, color, sex/gender, pregnancy, gender identity, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or other protected classification under applicable law. Thomson Reuters is an Equal Employment Opportunity Employer, a drug‑free workplace, and provides reasonable accommodations for qualified individuals with disabilities and sincerely held religious beliefs.

Learn more on how to protect yourself from fraudulent job postings here.

More information about Thomson Reuters can be found on thomsonreuters.com.

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Manager, Lead Research Scientist, Training Data (Foundational Research) employer: Thomson Reuters

Thomson Reuters Labs is an exceptional employer, offering a dynamic and collaborative work environment where innovation thrives. With access to vast datasets and cutting-edge technologies, employees are empowered to lead impactful research in foundational machine learning while enjoying a flexible hybrid work model and comprehensive benefits that support work-life balance and career growth. The company fosters a culture of inclusion and continuous learning, making it an ideal place for those looking to make a meaningful contribution in the AI field.
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Contact Detail:

Thomson Reuters Recruiting Team

StudySmarter Expert Advice 🤫

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

✨Tip Number 1

Network like a pro! Reach out to your connections in the industry, attend relevant meetups, and engage with professionals on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

✨Tip Number 2

Prepare for interviews by researching the company and its projects. Familiarise yourself with their recent work in AI and machine learning. This will not only help you answer questions but also show your genuine interest in their mission.

✨Tip Number 3

Practice your pitch! Be ready to explain your experience and how it aligns with the role of Research Scientist Manager. Highlight your leadership skills and any innovative projects you've led that relate to foundational research.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team at Thomson Reuters Labs.

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

Machine Learning
Natural Language Processing (NLP)
AI Systems Development
Deep Learning Frameworks (e.g. PyTorch, JAX, TensorFlow)
Data Curation
Synthetic Data Generation
Large Language Models (LLMs)
Algorithm Development
Research Publication
Team Leadership
Project Management
Collaboration
Communication Skills
Agile Methodologies
Cloud Computing (e.g. Amazon AWS, MS Azure, Google Cloud)

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the role of Research Scientist Manager. Highlight your experience in leading teams and your strong publication record. We want to see how your background aligns with our focus on foundational machine learning research.

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for AI research and how you can contribute to our team. Be sure to mention specific projects or experiences that demonstrate your innovative thinking and leadership skills.

Showcase Your Technical Skills: Don’t forget to highlight your technical expertise, especially with deep learning frameworks like PyTorch or TensorFlow. We’re looking for someone who can roll up their sleeves and get involved in coding and experiments, so make sure we see that in your application!

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. Plus, you’ll find all the details about the role and our company culture there!

How to prepare for a job interview at Thomson Reuters

✨Know Your Research

Dive deep into the latest advancements in foundational machine learning and AI systems. Be prepared to discuss your own research, especially any publications in top-tier conferences. This shows your passion and expertise, which is crucial for a role that involves leading cutting-edge research.

✨Showcase Your Leadership Skills

As a potential manager, it's essential to demonstrate your ability to inspire and guide teams. Share specific examples of how you've mentored others or led projects in the past. Highlighting your management experience will help you stand out as a candidate who can effectively lead a diverse global team.

✨Be Ready to Discuss Collaboration

Collaboration is key in this role, so be prepared to talk about your experiences working with cross-functional teams. Mention any partnerships with academic institutions or industry experts, and how these collaborations have contributed to successful outcomes in your projects.

✨Prepare for Technical Questions

Expect to face technical questions related to deep learning frameworks and large-scale model training. Brush up on your knowledge of tools like PyTorch, TensorFlow, and cloud platforms. Being able to discuss your hands-on experience with these technologies will show that you're ready to hit the ground running.

Manager, Lead Research Scientist, Training Data (Foundational Research)
Thomson Reuters

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