Thomson Reuters is looking to solve complex business problems using Generative AI and Machine Learning to deliver a workable solution that meets customer requirements and technical capabilities.
Requirements
- Proficiency in Python
- At least 3+ years practical, relevant experience building AI/ML products and applications
- Recent demonstratable experience using Generative AI technologies such as RAG patterns, ReAct, LangChain etc
- Solid software engineering skills and experience
- Hands on coding experience on AI/ML projects
- Experience designing, developing, and implementing machine learning models and algorithms
- Familiarity with common NLP use cases such as chatbot development and information retrieval (RAG), language translation, NER, summarization and topic modeling
Responsibilities
- Experiment and Develop: drive the end-to-end model development lifecycle, championing best practices to ensure reproducible research and well-managed software delivery.
- Collaborate: work on a collaborative cross-functional team, share information, value diverse ideas, and partner effectively with colleagues across the globe.
- Deliver: translate complex business problems into projects with clearly defined scope, and be accountable for timely, well-managed deliverables.
- Innovate: try new approaches and learn new technologies, foster innovative ideas to solve real-world challenges, and iterate on improvement rapidly.
- Inspire: be a proactive communicator who is excited to share work, articulate and compelling in describing ideas to both technical and non-technical audiences.
- Develop and deploy generative AI and machine learning applications
- Support product development efforts, including model development and monitoring, ML management and DevOps
Other
- Master’s or Bachelor’s in a relevant discipline
- Ability to obtain and maintain a U.S. national security clearance
- U.S. Citizenship essential to comply with government contract/agency or department of Federal Government requirements
- Outstanding communication and data-driven decision-making collaboration with Product + Business Stakeholders
- Flexibility and ability to work in a fast-paced, agile environment managing uncertainty and ambiguity
