Are you a curious and open-minded individual with an interest in programming and machine learning? Thomson Reuters Labs in Toronto is seeking an ML/NLP scientist intern with a passion for problem-solving using state-of-the-art Machine Learning and Natural Language Processing techniques.
What does Thomson Reuters Labs do? We experiment, we build, we deliver. We support the organization and our customers through applied research and development of new products and technologies. The Labs innovate collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News. We undertake a diverse portfolio of projects today while investing in long-term research for the future.
As an Applied Scientist Intern, you will be part of a diverse and interdisciplinary global team of experts. We hire specialists in Information Retrieval, Natural Language Processing, and Machine Learning, as well as Engineering and Design to drive the company’s digital and AI transformation. Thomson Reuters Labs is known for consistently delivering successful data-driven Artificial Intelligence solutions in support of high-growth products that serve Thomson Reuters customers in new and exciting ways.

ABOUT THE ROLE:

As an Applied Scientist Intern, you will:

• Experiment and Develop: You can be involved in the entire model development lifecycle, building, testing, and delivering high-quality solutions.
• Collaborate: Working on a collaborative cross-functional team, you will learn from and partner with colleagues across the globe.
• Innovate: You will have the opportunity to try new approaches and learn new technologies. You will contribute ideas and work on solving real-world challenges.

You are fit for the Applied Scientist Intern role if your background includes some of the following:

• Be currently enrolled in a PhD program relevant discipline or Master’s program with research experience.
• Have an understanding and experience with Natural Language Processing, and/or Machine Learning methods including Large Language Models.
• Have experience creating and evaluating experiments related to Machine Learning or Large Language Models.
• Have proficiency in implementing solutions using Python, DL/ML/NLP frameworks, and relevant tools.
• Have experience in using code collaboration and versioning systems such as GitHub.
• Have familiarity with cloud tools such as Amazon AWS, MS Azure, or Google Cloud.
• Are comfortable working with unstructured datasets and are knowledgeable about tools and techniques for data cleaning and processing.
• Have a data-driven problem-solving and decision-making mindset.
• Have good communication skills and the ability to work collaboratively as part of a team