Manager, Research Science (Foundational Research, Machine Learning)

Thomson Reuters - Frisco, TX

Full-time - Manager

Frisco, TX

10,001+ employees

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About the position

The Research Scientist Manager at Thomson Reuters Labs is responsible for leading teams in foundational machine learning research, focusing on advanced algorithms and training techniques for Large Language Models (LLMs). This role involves strategic planning, innovation, and collaboration with both internal teams and academic partners to solve complex real-world problems using data-rich environments. The manager will oversee the entire research and model development lifecycle, ensuring high-quality outputs and contributing to the academic community through publications and presentations.

Responsibilities

• Lead strategic planning, hiring, and management in foundational research.
• Innovate and create new state-of-the-art ML/NLP/IR/GenAI approaches.
• Experiment and develop throughout the research and model development lifecycle.
• Collaborate with a global team of research engineers and academic partners.
• Communicate technical findings through seminars, lectures, and publications.

Requirements

• PhD in a relevant discipline.
• Strong publication record in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL).
• Familiarity with deep learning frameworks (e.g., PyTorch, JAX, TensorFlow).
• Experience in ML Research beyond completing a PhD (e.g., supervision, industry experience).
• Excellent communication skills for reporting and presenting research findings.
• Curious and innovative disposition for devising novel algorithmic solutions.
• Good social skills to motivate and mentor team members.
• Comfortable in fast-paced, agile environments.

Nice-to-haves

• High-impact publications in top-tier conferences or influence in the research community.
• 5+ years of hands-on experience leading teams in advanced ML/NLP/IR systems.
• Extensive experience with deep learning and large-scale model training.
• Experience with state-of-the-art research topics in LLMs.
• Strong software and infrastructure engineering skills.
• Experience training large-scale models over distributed nodes with cloud tools.

Benefits

• Access to large datasets and computing resources.
• Opportunities for publishing research findings.
• Collaboration with world-leading academic institutions.