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Thomson Reuters

Legal, financial data, and media services

Generative AI & Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeMcLean, VA, USA

About the Job

Requirements

  • A master's or bachelor's degree in a relevant discipline, or equivalent relevant experience in lieu of a degree.
  • Proficiency in Python.
  • At least 3 years of practical, relevant experience building artificial intelligence or machine learning products and applications, including recent demonstrable experience using generative AI technologies such as retrieval-augmented generation patterns, ReAct, and LangChain for document summarization, knowledge graphs, information extraction, or analysis.
  • Solid software engineering skills and experience.
  • Experience as a technical leader, including ideating with product stakeholders, handling uncertainty and ambiguity in problem statements and paths to success, decomposing complex problems into tractable components with iterative improvements, formulating research and development plans, coordinating and working with others, and communicating progress and plans to varied stakeholders.
  • Hands-on coding experience on artificial intelligence or machine learning projects in the current role, and experience designing, developing, and implementing machine learning models and algorithms.
  • Ability to obtain and maintain a U.S. national security clearance.
  • U.S. citizenship is required to comply with government contract, agency, or federal department requirements.

Responsibilities

  • Drive the end-to-end model development lifecycle and champion best practices to ensure reproducible research and well-managed software delivery.
  • Collaborate on a cross-functional team, share information, value diverse ideas, partner with colleagues, mentor teammates, and work with product teams to integrate and deploy work into production environments.
  • Translate complex business problems into projects with clearly defined scope and deliver timely, well-managed deliverables.
  • Try new approaches and learn new technologies, foster innovative ideas to solve real-world challenges, and rapidly iterate on improvements using a fail-fast and continuous-learning approach.
  • Communicate work and ideas to technical and non-technical audiences, and help lead enterprise-wide adoption of artificial intelligence.

Desired Qualifications

  • At least 6 years of practical experience using artificial intelligence and machine learning to solve diverse or ambiguous problems in academia or industry.
  • Experience with artificial intelligence agent frameworks and patterns.
  • Familiarity with natural language processing use cases such as chatbot development, information retrieval using retrieval-augmented generation, language translation, named entity recognition, summarization, and topic modeling.
  • Familiarity with large language model training and efficient fine-tuning techniques, including parameter-efficient fine-tuning, Low-Rank Adaptation, and quantization.
  • Experience with natural language processing and computer vision libraries such as PyTorch, TensorFlow, scikit-learn, spaCy, Hugging Face Transformers and Diffusers, OpenAI, LangChain, Semantic Kernel, and OpenCV.
  • Experience using cloud solutions such as Amazon Web Services and Azure to build and deploy applications.
  • Experience working in a fast-paced, agile environment managing uncertainty and ambiguity.
  • Proficiency in Python and experience delivering minimum viable products in a large enterprise environment.
  • Experience developing libraries and application programming interfaces for others to use.
  • Experience communicating and making data-driven decisions in collaboration with product and business stakeholders.
  • Experience across diverse problem spaces, companies, and cultures.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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