Applied Scientist Intern — ML/NLP Research & Innovation

Thomson Reuters; New York (NY); On-site; USD 28,000 - 41,000; Full time

Job summary

Thomson Reuters Labs is seeking an Applied Scientist Intern to work on ML/NLP projects with state-of-the-art techniques. The role involves a full lifecycle from experimentation to deployment, collaborating with a global team across Legal, Tax & Accounting, Government, and Reuters News domains.

Ideal candidates are pursuing a PhD or a Master’s with research experience, skilled in Python and NLP libraries, and comfortable handling unstructured data while communicating effectively within a team.

Qualifications

• Currently enrolled in a PhD program or a Master's with research experience.
• Experience with NLP/ML methods, including Large Language Models.
• Experience with model training, fine-tuning, and evaluation of ML/LLM experiments.
• Proficiency in Python and cloud experience (prefer AWS).
• Experience with ML/NLP libraries (PyTorch, TensorFlow, Scikit-learn, spaCy, LangChain, HuggingFace).
• Comfort with unstructured data and data cleaning/processing techniques.
• Strong communication and collaborative skills.

Responsibilities

• Experiment and develop: build, test, and deliver ML/NLP solutions across the lifecycle.
• Collaborate with a cross-functional global team to share insights and learn.
• Innovate by trying new approaches and technologies to solve real-world challenges.

Skills

NLP/ML concepts

Python

AWS Cloud

PyTorch/TensorFlow

Education

PhD candidate or Master's with research

Tools

PyTorch

TensorFlow

Scikit-learn

spaCy

LangChain

HuggingFace

Job description

Thomson Reuters Labs is seeking an Applied Scientist Intern to work on ML/NLP projects with state-of-the-art techniques. The role involves a full lifecycle from experimentation to deployment, collaborating with a global team across Legal, Tax & Accounting, Government, and Reuters News domains.

Ideal candidates are pursuing a PhD or a Master’s with research experience, skilled in Python and NLP libraries, and comfortable handling unstructured data while communicating effectively within a team.