Transform information retrieval systems as an Applied Scientist at Thomson Reuters. Engage in neural search techniques to optimize legal content accessibility across platforms like Westlaw and CoCounsel.

This role requires a strong foundation in applied science, focusing on design and deployment of production-grade search systems. With over 5 years of industry experience, you will focus on query understanding and re-ranking strategies critical for maximizing search relevance. Your work will significantly influence the legal sector by enhancing content discovery.

Key Responsibilities:
• Design production-ready neural search systems for legal applications
• Develop advanced models for document re-ranking
• Build evaluation frameworks for search performance




• Drive architecture decisions affecting index and retrieval strategies
• Collaborate closely with engineering for system scalability

Requirements:
• Advanced degree (PhD or Master's) in relevant fields
• 5+ years of post-degree experience in shipping search systems
• Research publications in high-impact venues
• Robust proficiency in Python; knowledge of PyTorch
• Hands-on experience with deep learning and neural IR

Utilize your skills in AI and retrieval systems to revolutionize legal information access at Thomson Reuters.
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📌 Applied Scientist specializing in Information Retrieval (Ontario)
🏢 Thomson Reuters
📍 Ontario