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Thomson Reuters

Legal, financial data, and media services

Director of Applied Research: Information Retrieval

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Information Retrieval, or a closely related field is required.
  • At least 8 years of industry experience building and deploying production AI systems at scale is required.
  • A proven track record of taking machine learning and AI solutions from research to production-grade software with measurable business impact is required.
  • A strong publication record in leading venues such as SIGIR, NeurIPS, ICLR, ACL, EMNLP, KDD, WWW, or comparable conferences is required.
  • Demonstrated ability to build, mentor, and manage high-performing teams of engineers and scientists is required.
  • Experience leading cross-functional initiatives and influencing technical strategy across research, engineering, and product organizations is required.
  • Deep hands-on experience in several of the following areas is required: information retrieval and search, including semantic search, ranking algorithms, retrieval optimization, search relevance, and evaluation methodologies; retrieval-augmented generation systems, grounding techniques, and answer quality assurance; agentic retrieval systems, tool-using retrieval agents, multi-step reasoning for search, and autonomous information discovery; natural language processing tasks including named entity recognition, information extraction, question answering, and advanced language understanding; large language models and generative AI, including prompt engineering, fine-tuning, model evaluation, and production deployment of LLM-based applications; knowledge graphs and knowledge systems; production AI development using Python, PyTorch, Hugging Face, and modern MLOps practices; and cloud-native AI deployment and operation using AWS, Azure, or equivalent platforms.
  • A demonstrated desire to learn and embrace emerging technologies in the AI and machine learning landscape is required.
  • A fundamental understanding of the software development life cycle and hands-on programming experience in languages such as Python, Java, TypeScript, or JavaScript is required.
  • The candidate should understand how to translate between research and engineering languages and methodologies, translate complex customer problems into solutions, work with ambiguity, and operate in diverse, agile, interdisciplinary environments.

Responsibilities

  • Define and drive the technical vision for AI-powered search, discovery, and knowledge systems.
  • Set the strategic direction for Information Retrieval research and innovation and establish technical direction for retrieval, ranking, semantic search, retrieval-augmented generation, and agentic retrieval capabilities.
  • Design and optimize retrieval architectures using embeddings, reranking, hybrid search, knowledge graphs, and contextual retrieval techniques.
  • Build evaluation frameworks and benchmarks for search quality, relevance, answer quality, and real-world business impact.
  • Contribute to the global Labs engineering strategy and methodology through adoption of emerging AI and machine learning technologies and industry best practices.
  • Hire, train, and manage a highly skilled team spanning cloud engineering, machine learning engineering, data engineering, and AI research.
  • Mentor scientists and engineers, establish best practices for production AI development and deployment, and develop team members' technical depth in information retrieval, natural language processing, generative AI, and large-scale AI systems.
  • Foster collaboration, innovation, and continuous learning across the global Labs organization.
  • Lead development of enterprise-grade retrieval, ranking, natural language processing, and knowledge-based AI solutions integrated with Thomson Reuters products.
  • Partner with Product and Engineering teams to translate customer needs and domain-specific challenges into scalable AI applications.
  • Establish channels between Labs research and product technology organizations to transfer innovation into production systems.
  • Apply modern development practices across the software development life cycle, from experimentation and deployment to operational excellence.
  • Use automation, system monitoring, MLOps, and cloud-native AI applications on AWS, Azure, or equivalent platforms.
  • Identify opportunities to improve existing work or generate business value through AI and machine learning innovation.
  • Influence the global project portfolio and investment decisions using applied AI expertise and domain knowledge.
  • Provide strategic input to product and modernization roadmaps, identifying and articulating AI-driven opportunities.
  • Translate complex customer problems in legal, tax, news, and corporate domains into successful AI solutions.
  • Engage across cross-functional teams, share knowledge, build relationships with technology and product leaders, and secure alignment and paths to market for AI-powered initiatives.
  • Communicate across research and engineering methodologies and languages.

Desired Qualifications

  • Experience building enterprise search, discovery, or research-assistance platforms is preferred.
  • Experience in Legal, Tax and Accounting, Risk, Financial Services, or other complex professional domains is preferred.
  • Experience with hybrid search, vector databases, recommendation systems, and large-scale retrieval platforms is preferred.
  • Experience deploying and operating AI solutions using Azure ML, Azure AI Foundry, AWS SageMaker, or similar cloud platforms is preferred.
  • Experience leading large-scale AI initiatives and building diverse, geographically distributed teams is preferred.
  • Familiarity with MLOps frameworks, containerization, and modern DevOps practices for AI systems is preferred.

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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