Thomson Reuters
Lead Applied Scientist, Search & Information Retrieval
$148K–$274K
United States of America, New York, New York +1 · Remote · Full-time · Posted Oct 16, 2026
- Location
- United States of America, New York, New York
Canada, Toronto, Ontario - Experience
- 8+ years of industry experience; the description also states 8+ years of post-degree industry experience.
- Education
- PhD in Computer Science, Information Retrieval, AI, Machine Learning, NLP, or a related field is listed as preferred; the description also says the candidate holds a PhD in a related field.
About the job
Leads the design, development, evaluation, and production deployment of large-scale search and information retrieval systems for Thomson Reuters products and content.
What you'll do
- Design and deploy search architectures, indexing and ingestion pipelines, and ranking systems for large collections of legal, tax, and enterprise content.
- Improve retrieval quality and measure search performance through semantic and hybrid retrieval, query understanding, relevance optimization, and evaluation frameworks.
- Lead technical decisions, partner with engineering and product teams, advise senior leadership, and mentor applied scientists and machine learning practitioners.
What they ask for
- 8+ years of industry experience building production search, information retrieval, ranking, or recommendation systems.
- Publications at SIGIR, ACL, EMNLP, NeurIPS, ICLR, KDD, WWW, or equivalent venues.
- Strong production Python skills and experience with PyTorch, Hugging Face Transformers, and distributed model development.
- Hands-on experience with search architecture, indexing and ingestion, ranking and re-ranking, retrieval evaluation, and LLM-enhanced retrieval.
Nice to have
- Experience in legal, regulatory, tax, scientific, or other text-heavy domains; large enterprise knowledge repositories; or self-service search platforms.
- Experience with Elasticsearch, OpenSearch, Solr, Vespa, AzureML, AWS SageMaker, or agentic AI systems incorporating retrieval.
Pay
$147,600 USD - $274,200 USD (base salary); $140,000 CAD - $175,000 CAD (base salary)
Tools
Python, PyTorch, Hugging Face Transformers, Elasticsearch, OpenSearch, Solr, Vespa, AzureML
AI focus
Builds LLM-enhanced ranking and retrieval, RAG architectures, retrieval optimization, and potentially agentic AI systems incorporating retrieval; provides technical input on AI strategy.
Model-written summary · the original posting is authoritative