Research Engineer, Data, Thomson Reuters

• Relevant degree in a technical discipline
• Interest in & experience working with (applied) machine learning, e.g. few-shot learning with out-of-the-box language models, training of smaller NLP classifiers, etc
• Excellent programming, debugging and system design skills
• Excellent communication skills to report and present software designs and findings clearly, both orally and in writing
• Curious and innovative disposition capable of devising novel, well-founded algorithmic solutions to relevant problems
• Self-driven attitude and ability to work with limited supervision
• Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra)
• Experience with data pipeline orchestration tools
• Experience with cloud-based data platforms such as AWS, GCP, or Azure (e.g., S3, BigQuery, Azure Data Lake Storage)
• Comfortable working in fast-paced, agile environments, managing uncertainty and ambiguity

Desirable

• As a Research Engineer, you will be part of a diverse global team of experts. We hire worldleading specialists in SWE /Applied ML, as well as Research, to drive the company’s leading internal AI model development, fueled by an unprecedented wealth of data and powered by cutting-edge technical infrastructure.
• You will have the opportunity to contribute to a data curation & filtering system combining the best of real-world scalable data processing systems combined with the latest insights into what training data leads to the best LLMs.
• Thomson Reuters Labs is known for consistently delivering successful datadriven Artificial Intelligence solutions in support of high-growth products that serve Thomson Reuters customers in new and exciting ways
• Innovate: You will work at the very cutting edge of AI Research at an institution with some of the richest data sources in the world. Through your work, you will help us make the best use of this resource, in a dynamic flywheel that connects data collection & annotation with model training and expert evaluation, helping us continuously improve our training data. You will also develop novel performance-driven data sub-selection methods together with the latest training insights from our researchers
• Engineer and Develop: Design, develop, and optimize scalable data pipelines to support LLM training and evaluation. You will also help us develop this in a robust and testable way, through careful source control and a solid back-up system for various data versioning methods
• Collaborate: Working on a collaborative global team of engineers and scientists both within Thomson Reuters and our academic partners at world-leading universities. In addition, you will work closely with world experts in the legal domain, which can provide feedback to your work and/or evaluate your outputs or annotate training data