Research Engineer Intern

Thomson Reuters is a global leader in providing trusted content and technology solutions. They are seeking a Research Engineering Intern to contribute to software development and innovation in AI and machine learning, working collaboratively with a diverse team to drive digital transformation.

Responsibilities

• Develop and Delivery – You will apply modern software development practices to building, testing, and delivering high-quality solutions. You will be involved in the entire software development lifecycle
• Build Scalable ML Solutions – You will create large-scale data processing pipelines to help researchers build and train novel machine learning algorithms. You will develop high-performing, scalable systems in the context of large online delivery environments
• Collaborate – Working on a collaborative cross-functional team of applied scientists and engineers, 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, create Minimum Viable Products, and work on solving real-world challenges

Skills

• Pursuing a Master's or Bachelor's degree in Computer Science, Information Technology, or a related discipline
• Proficiency in Python and a deep understanding of related software development stacks and ecosystems
• Ability to write clean, reusable, maintainable, and well-tested code
• Experience with using code collaboration and versioning systems such as GitHub
• Desire to learn and embrace new and emerging technologies
• Strong communication and collaboration skills
• Understanding of CI/CD, DevOps, and SDLC concepts for application development
• Understanding of Natural Language Processing, and/or Machine Learning methods, including Large Language Models
• Familiarity with cloud platforms (any of AWS, Azure, Google Cloud) and a basic understanding of MLOps tools and practices
• Familiarity with working with unstructured datasets and knowledge about tools and techniques for data cleaning and processing
• Keen interest in real-world applications and impact

Benefits

• Career Development and Growth
• Culture
• Social Impact
• Making a Real-World Impact

Company Overview