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Director of Applied Research
Thomson Reuters. Define and drive the technical vision and strategy for AI-powered search, discovery, and knowledge systems .
Tech Stack
Tools & technologiesAWSAzureCloudJavaJavaScriptPythonPyTorchSDLCTypeScript
About the role
Key responsibilities & impact- Define and drive the technical vision and strategy for AI-powered search, discovery, and knowledge systems
- Set strategic direction for Information Retrieval research and innovation
- Establish technical direction for retrieval, ranking, semantic search, RAG, and agentic retrieval capabilities
- Design and optimize retrieval architectures using embeddings, reranking, hybrid search, knowledge graphs, and contextual retrieval
- Build evaluation frameworks and benchmarks for search quality, relevance, answer quality, and business impact
- Contribute to global Labs engineering strategy and methodology through emerging AI/ML technologies and best practices
- Hire, train, mentor, and manage teams across cloud engineering, machine learning engineering, data engineering, and AI research
- Establish best practices for production AI development and deployment
- Develop team members’ technical depth in information retrieval, NLP, generative AI, and large-scale AI systems
- Lead development of enterprise-grade retrieval, ranking, NLP, and knowledge-based AI solutions integrated with Thomson Reuters products
- Partner with Product and Engineering teams to translate customer needs into scalable AI applications
- Transfer research innovation into production systems
- Apply modern software development practices from experimentation through deployment and operational excellence
- Drive automation, system monitoring, MLOps, and cloud-native AI applications
- Identify opportunities for AI/ML innovation and new business value
- Influence project portfolio and investment decisions
- Provide strategic input to product and modernization roadmaps
- Translate customer problems in legal, tax, news, and corporate domains into successful AI solutions
- Engage cross-functionally with technology and product leaders
- Translate between research and engineering methodologies and languages
- Secure alignment and clear paths to market for AI-powered initiatives
Requirements
What you’ll need- 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 taking machine learning and AI solutions from research to production-grade software with measurable business impact
- Strong publication record in leading venues such as SIGIR, NeurIPS, ICLR, ACL, EMNLP, KDD, WWW, or comparable conferences
- 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
- Entrepreneurial mindset with confidence in making independent decisions and driving initiatives
- Exceptional communication, collaboration, and stakeholder management skills
- Deep expertise in Information Retrieval, Search, Natural Language Processing, and Generative AI
- Experience with semantic search, ranking algorithms, retrieval optimization, search relevance, and evaluation methodologies
- Experience designing and optimizing RAG systems, grounding techniques, and answer quality assurance
- Experience with agentic retrieval systems, tool-using retrieval agents, multi-step reasoning, and autonomous information discovery
- Experience with NER, information extraction, question answering, and advanced language understanding
- Experience with prompt engineering, fine-tuning, model evaluation, and production deployment of LLM applications
- Experience designing, constructing, and leveraging knowledge graphs
- Hands-on experience with Python, PyTorch, Hugging Face, and modern MLOps practices
- Proficiency in AWS, Azure, or equivalent cloud platforms
- Understanding of the SDLC and hands-on programming experience with Python, Java, TypeScript, or JavaScript
- Preferred: experience with enterprise search, complex professional domains, hybrid search, vector databases, recommendation systems, Azure ML, Azure AI Foundry, AWS SageMaker, MLOps frameworks, containerization, DevOps, and geographically distributed teams
Benefits
Comp & perks- Flexible work arrangements, including work from anywhere for up to 8 weeks per year
- Grow My Way programming and skills-first development support
- Flexible vacation
- Two company-wide Mental Health Days off
- Headspace app access
- Retirement savings
- Tuition reimbursement
- Employee incentive programs
- Mental, physical, and financial wellbeing resources
- Two paid volunteer days off annually
- Pro-bono consulting and ESG initiative opportunities
- Health, dental, vision, disability, and life insurance programs
- 401(k) plan with company match
- Sick and safe paid time off
- Paid holidays, including two company mental health days
- Parental leave
- Sabbatical leave
- Optional hospital, accident, and sickness insurance
- Optional life and AD&D insurance
- Flexible Spending and Health Savings Accounts
- Fitness reimbursement
- Employee Assistance Program
- Group Legal Identity Theft Protection benefit
- 529 Plan access
- Commuter benefits
- Adoption & Surrogacy Assistance
- Employee Stock Purchase Plan
- Eligible for an Annual Bonus based on enterprise and individual performance