Senior Research Scientist (Foundational Research, Machine Learning)

Thomson Reuters - Ann Arbor, MI

Full-time - Entry Level

Hybrid - Ann Arbor, MI

10,001+ employees

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About the position

The Senior Research Scientist at Thomson Reuters Labs is responsible for conducting foundational machine learning research and developing innovative solutions in a collaborative environment. This role involves experimenting with state-of-the-art ML/NLP/GenAI approaches, mentoring by leading experts, and contributing to the research and development of proprietary AI models. The position offers opportunities to publish research findings and engage in the entire model development lifecycle, addressing real-world challenges using extensive data resources.

Responsibilities

• Innovate new ML/NLP/IR/GenAI approaches and contribute ideas to solve real-world challenges.
• Participate in the entire research and model development lifecycle, including brainstorming, building, testing, and delivering reports.
• Collaborate with a global team of research engineers and academic partners.

Requirements

• PhD student or recent graduate with research experience in a technical discipline.
• First-author publications at relevant venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, or similar.
• Excellent communication skills for reporting and presenting research findings clearly, both orally and in writing.
• Curious and innovative disposition capable of devising novel algorithmic solutions to relevant problems.
• Self-driven attitude and ability to work with limited supervision.
• Comfortable working in fast-paced, agile environments, managing uncertainty and ambiguity.

Nice-to-haves

• Experience with large language models (LLMs) such as alignment, hallucination detection, model compression, and efficient fine-tuning.
• Familiarity with cloud tools like Amazon AWS, MS Azure, or Google Cloud.
• Previous experience working on large-scale machine learning systems.
• Strong software and/or infrastructure engineering skills, evidenced by contributions to open-source libraries.

Benefits

• Hybrid Work Model with flexible working environment.
• Comprehensive benefit plans including flexible vacation and mental health days off.
• Access to resources for mental, physical, and financial wellbeing.
• LinkedIn Learning access and internal Talent Marketplace opportunities.
• Two paid volunteer days annually and ESG initiatives for local impact.