Research GraphRAG and large language models through a paid twelve-month residency focused on legal and regulatory compliance challenges.
As a Machine Learning Resident, you will report to an Amii Scientist and consult regularly with Ultimarii’s client team. You will research graph retrieval strategies, knowledge graphs, and applied natural language processing. The project supports an existing hybrid retrieval-augmented generation pipeline.
Key Responsibilities:
- Integrate a graph knowledge layer into an existing hybrid RAG pipeline
- Build knowledge graphs from unstructured regulatory and legal text
- Benchmark graph retrieval against baseline hybrid search pipelines
- Develop and evaluate features for large language model applications
- Present findings and progress to client stakeholders
Requirements:
- Graduate degree or higher in computing science, machine learning, or engineering
- Research experience in NLP, knowledge graphs, and LLMs
- Experience with LLM use cases and RAG architectures
- Proficiency in Python and related machine learning frameworks
- Legal eligibility to work in Canada
Apply your Python, NLP, knowledge graph, and LLM expertise to GraphRAG research with Ultimarii and Amii.