Applied Scientist, Search & Information Retrieval
Core
Building and deploying production-grade neural search systems for legal and professional content products like Westlaw and PracticalLaw.
Role type
Senior Applied Scientist (Search & Information Retrieval)
Builds
Production neural search systems, retrieval models, and re-ranking pipelines for legal databases.
Domain
Legal technology, Information Retrieval, NLP
Deliverable
production ML models
Required skills
Neural IR, Deep Learning, NLP, Python, PyTorch, Model Deployment, Evaluation Framework Design, RAG System Design, Large Language Model Post-training
Preferred skills
Legal domain search, Agentic retrieval architectures, AzureML, AWS SageMaker
Technologies
PyTorch, DeepSpeed, Torchtune, LlamaFactory, Vector Databases, Cross-encoders, Bi-encoders, Transformers
Responsibilities
Design and deploy end-to-end neural search systems including dense retrieval and hybrid search; Develop models for query understanding and document re-ranking; Build evaluation frameworks using expert annotation and synthetic data; Drive technical decisions on retrieval architecture and ranking models; Partner with engineering on delivery and scale; Contribute to published research at top venues.
Seniority
Senior, hands-on IC
