Director of Applied Research

Job Description:

Director of Applied Research, Information Retrieval

Thomson Reuters Labs

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.

Key Responsibilities

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 AI solutions at scale
• •Emerging Technologies : A demonstrated desire to learn and embrace new and emerging technologies in the AI/ML landscape

Ideal Candidate Profile

• •You understand and can translate between research and engineering languages and methodologies
• •You bring a strong product mindset and understand how to translate complex customer problems into successful solutions
• •You have a fundamental understanding of the SDLC and hands-on experience in programming languages such as Python, Java, TypeScript, or JavaScript
• •You are comfortable with ambiguity, creative in redirecting when reaching dead ends, and embrace continuous evolution of your skills
• •You thrive in diverse, agile, and interdisciplinary environments with a strong sense of urgency

Preferred Qualifications

• •Experience building enterprise search, discovery, or research-assistance platforms
• •Experience within Legal, Tax & Accounting, Risk, Financial Services, or other complex professional domains
• •Experience with hybrid search, vector databases, recommendation systems, and large-scale retrieval platforms
• •Experience deploying and operating AI solutions using Azure ML, Azure AI Foundry, AWS SageMaker, or similar cloud platforms
• •Experience leading large-scale AI initiatives and buildi