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Job description
Job Description
Director of Applied Research, Information Retrieval
About Thomson Reuters Labs
We experiment, build and deliver. Thomson Reuters Labs work across all business segments to discover what new products, services, and AI-driven solutions we can create for our customers. With access to over 60,000 TBs of legal, regulatory, news, and tax data, we are building the next generation of AI-powered knowledge systems that transform how professionals access, discover, and act on information.
You will join the global labs leadership team as a key leader shaping the technical vision and culture of Thomson Reuters' IR and AI research initiatives.
Key Responsibilities
As Director of Applied Research, you will define and drive the technical vision for AI-powered search, discovery, and knowledge systems that unlock value from Thomson Reuters' unique data assets. You will combine strategic leadership with hands‑on technical depth, building a world‑class team while directly contributing to cutting‑edge IR research and production‑grade solutions.
Define Technical Vision & Strategy
Set the strategic direction for Information Retrieval research and innovation at Thomson Reuters, positioning TR as a leader in retrieval‑based AI
Establish the technical direction for retrieval, ranking, semantic search, retrieval‑augmented generation (RAG), and agentic retrieval system capabilities
Design and optimize retrieval architectures leveraging 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 TR Labs engineering strategy and methodology through adoption of emerging AI/ML technologies and industry best practices
Build & Lead a High‑Performing Team
Hire, train, and manage a highly skilled team with expertise across cloud engineering, machine learning engineering, data engineering, and AI research
Mentor scientists and engineers while establishing best practices for production AI development and deployment
Foster a culture of collaboration, innovation, and continuous learning across the global labs organization
Develop team members' technical depth in information retrieval, NLP, generative AI, and large‑scale AI systems
Drive Production AI Solutions
Lead development of enterprise‑grade retrieval, ranking, NLP, and knowledge‑based AI solutions that integrate with Thomson Reuters products
Partner closely with Product and Engineering teams to translate customer needs and domain‑specific challenges into scalable AI applications
Establish robust channels between Labs research and product technology organizations, enabling effective transfer of innovation to production systems
Apply modern development practices across the entire software development lifecycle—from experimentation to deployment to operational excellence
Demonstrate proficiency in automation, system monitoring, MLOps, and cloud‑native AI applications on AWS, Azure, or equivalent platforms
Drive Strategy & Business Impact
Proactively identify opportunities where Labs can improve the status quo or generate new business value through AI/ML innovation
Influence the global project portfolio and investment decisions with your expertise in applied AI and domain knowledge
Provide strategic input to product and modernization roadmaps, particularly in identifying and articulating AI‑driven opportunities
Translate complex customer problems in legal, tax, news, and corporate domains into successful AI solutions
Continuously question why something needs to be done and for whom, maintaining a strong customer‑centric mindset
Be a Trusted Advisor
Actively engage across cross‑functional teams, sharing knowledge, valuing diverse ideas, and building relationships with technology and product leaders
Communicate effectively—translating between research and engineering methodologies and languages
Secure alignment and clear paths to market for AI‑powered initiatives
Required Qualifications
You are a recognized AI leader with deep expertise in Information Retrieval, Search, Natural Language Processing, and Generative AI. You have a proven track record of turning cutting‑edge research into production solutions that deliver measurable customer value, and you bring the rare combination of technical depth, engineering excellence, and strategic business acumen.
Core Qualifications
Education & Experience
PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Information Retrieval, or a closely related field
8+ years of industry experience building and deploying production AI systems at scale
Proven track record of successfully taking machine learning and AI solutions from research to production‑grade software with measurable business impact
A strong publication record in leading venues such as SIGIR, NeurIPS, ICLR, ACL, EMNLP, KDD, WWW, or comparable conferences
Leadership & Team Building
Demonstrated ability to build, mentor, and manage high‑performing teams of engineers and scientists
Experience leading cross‑functional initiatives and influencing technical strategy across research, engineering, and product organizations
An entrepreneurial mindset with confidence in making independent decisions and driving initiatives forward
Exceptional communication, collaboration, and stakeholder management skills
Technical Expertise
You bring deep hands‑on experience in several of the following areas:
Information Retrieval & Search: Semantic search, ranking algorithms, retrieval optimization, search relevance, and evaluation methodologies
Retrieval‑Augmented Generation (RAG): Design and optimization of RAG 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: Core NLP tasks including Named Entity Recognition (NER), Information Extraction, question answering, and advanced language understanding
Large Language Models & Generative AI: Prompt engineering, fine‑tuning, model evaluation, and production deployment of LLM‑based applications
Knowledge Graphs & Knowledge Systems: Design, construction, and leveraging of knowledge graphs for AI applications
Production AI Development: Hands‑on experience with Python, PyTorch, Hugging Face, and modern MLOps practices
Cloud‑Native AI: Proficiency in AWS, Azure, or equivalent cloud platforms for deploying and operating
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Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.