Thomson Reuters
Director of Applied Research
$198K–$368K
United States of America, New York, New York · Remote · Director · Full-time · Posted Oct 2, 2026
- Experience
- 8+ years of industry experience building and deploying production AI systems at scale.
- Education
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Information Retrieval, or a closely related field.
About the job
Leads applied research and production development for AI-powered information retrieval, search, discovery, and knowledge systems, while setting technical strategy and building a research and engineering team.
What you'll do
- Set technical direction for retrieval, ranking, semantic search, RAG, and agentic retrieval, including architectures and evaluation frameworks.
- Hire, mentor, and manage researchers and engineers; foster production AI development practices.
- Lead AI solutions from research into scalable products, partnering across Product and Engineering and shaping strategic investment and roadmaps.
What they ask for
- 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 record 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.
Nice to have
- Experience building enterprise search, discovery, or research-assistance platforms.
- Experience in Legal, Tax & Accounting, Risk, Financial Services, or other complex professional domains.
Pay
$198,200 USD - $368,000 USD (base salary)
Tools
Python, PyTorch, Hugging Face, AWS, Azure, Azure ML, Azure AI Foundry, AWS SageMaker
AI focus
Applied AI research and production systems for information retrieval, semantic search, ranking, RAG, agentic retrieval, NLP, generative AI, knowledge graphs, and large-scale AI applications.
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