Senior Machine Learning Engineer, Thomson Reuters

• Master’s degree in Machine Learning, Computer Science, Statistics, or a closely related quantitative field with a focus on machine learning or artificial intelligence
• 3+ years of professional machine learning engineering, applied machine learning, research engineering, or closely related software engineering experience
• Demonstrated hands-on experience building, training, and deploying machine learning models into production, including the ability to explain your individual contribution from model development through production deployment
• Strong practical experience with machine learning, natural language processing, and modern LLM architectures
• Experience with at least one of the following: information extraction, text generation/summarization, AI agents, or search
• Advanced Python programming skills and hands-on experience with machine learning frameworks such as PyTorch or TensorFlow
• Experience developing or fine-tuning language models or other machine learning models for specialized use cases or domains
• Experience designing and applying model evaluation methods and metrics to measure the performance and reliability of production machine learning systems
• Ability to translate product or business problems into machine learning solutions and clearly communicate technical decisions, trade-offs, and outcomes
• Strong problem-solving, collaboration, and ownership skills, with the ability to work effectively across technical and domain-focused teams

Desirable

• As a Senior Machine Learning Engineer, you will build and deploy production machine learning and large language model (LLM) systems that extract actionable insights from complex legal documents and data
• You will work on challenging natural language processing problems involving contractual language, information extraction, model-driven analysis, and comparisons across large collections of documents
• You will join a highly technical machine learning team and collaborate with machine learning engineers, legal subject matter experts, product engineers, and data and security partners
• This is a hands-on role for someone who has personally built, trained, evaluated, and deployed machine learning models into production and wants to apply that expertise to sophisticated real-world products
• Design, build, train, and deploy machine learning and LLM-based models and systems that solve complex natural language processing and document intelligence problems
• Develop production solutions for areas such as information extraction, text generation and summarization, AI agents, search, and document analysis
• Build scalable and reliable machine learning pipelines that support model training, evaluation, deployment, and ongoing production use
• Develop rigorous model evaluation frameworks and metrics to assess model quality, accuracy, reliability, drift, and potential bias
• Optimize model performance and resource utilization through experimentation, feature engineering, model selection, and tuning
• Translate complex business and product problems into practical machine learning solutions and take those solutions from experimentation through production deployment at scale
• Collaborate across machine learning, engineering, product, legal domain, data, and security teams to deliver reliable AI capabilities while protecting sensitive information

• End Date: December 25, 2026