Thomson Reuters is seeking a Lead Applied Scientist to transform how millions of legal, tax, and compliance professionals interact with information through intelligent agents that understand their domain, anticipate their needs, and evolve with their workflows.
Requirements
- PhD in Computer Science, Machine Learning, AI, or related field (or Master's with equivalent depth of experience)
- Strong software engineering capabilities with experience in production code, MLOps, and managed delivery pipelines
- Proven track record translating complex, ambiguous problems into successful AI applications
- Proficiency in AI evaluation, quality assessment, and observability for production systems
- Neuro-symbolic AI architectures that combine learning and reasoning
- Expertise in multi-modal modeling across diverse data types and representation formats
- Hands-on experience with knowledge representation, ontologies, and semantic reasoning systems
Responsibilities
- Design and deploy neuro-symbolic AI systems that seamlessly integrate neural learning with structured knowledge representation and ontologies
- Build multi-modal models that synthesize insights across text, documents, structured data, and domain-specific artifacts
- Explore the emergent intelligence at the intersection of GenAI and machine learning agents, creating autonomous systems that reason and act
- Develop adaptive domain-specific reasoning capabilities that understand the nuances of legal, regulatory, and financial contexts
- Own and lead end-to-end research deliverables—from ideation and experimentation to production deployment
- Establish comprehensive AI evaluation frameworks, quality assessment methodologies, and observability systems that ensure reliability, fairness, and transparency
- Leverage advanced information retrieval techniques, prompting workflows, and model training strategies to optimize solutions
Other
- 7+ years building production IR/NLP systems for commercial applications with demonstrated business impact
- Outstanding communication skills—you translate complex technical concepts for diverse audiences
- Proven success collaborating with Product, Engineering, and Business stakeholders in agile environments
- Strong problem-solving and analytical thinking with a bias toward action and iteration
- PhD or Master's degree in relevant field
