Staff Applied Scientist – Search

Staff Applied Scientist – Search

Requirements

• A Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, or a related field (or equivalent practical experience).
• Strong expertise in machine learning algorithms, statistical methods, and optimisation techniques.
• A strong track record of scientific research (in any field), and have done work on information retrieval, knowledge representation and reasoning, structured knowledge extraction, or large-scale data analytics.
• Ability to view research and engineering as two sides of the same coin, with every team member writing code, designing and running experiments, and interpreting results.
• Experience (or desire to be) working in multi-disciplinary teams.

Responsibilities

• Develop and advance knowledge extraction and representation methods, particularly in structured knowledge extraction from legal texts and images, knowledge graphs/ontology engineering, legal knowledge base construction, and specialised embedding methods for multimodal content in the legal domain.
• Develop methods for retrieval and reasoning over legal knowledge bases and systems, including hybrid search approaches combining symbolic and neural techniques, and query understanding and rewriting for legal search.
• Perform fine-tuning and reinforcement learning to teach language models how to interact with new information architectures.
• Build ‘hard’ eval sets to help identify failure modes of how language models work with legal data.
• Build infrastructure for running experiments and visualising results.
• Work with colleagues to communicate results internally and publicly.
• Stay updated with the latest research in machine learning, AI, knowledge representation and retrieval to bring innovative solutions to the table.
• Mentor junior researchers and contribute to building a collaborative, knowledge-sharing culture.

Preferred Qualifications

No preferred qualifications provided.