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Machine Learning Resident – Client: Ultimarii
Posted 4 days ago
About the role
- Machine Learning Resident researching GraphRAG and knowledge graphs for Ultimarii’s AI-powered project-management products. Benchmarking retrieval strategies and advancing a production LLM application.
Responsibilities
- Report to an Amii Scientist and regularly consult with the Client team
- Research, evaluate, and benchmark graph retrieval strategies to enhance an existing hybrid RAG pipeline with a GraphRAG layer
- Research methodologies for building and populating domain-specific knowledge graphs from unstructured regulatory and legal text
- Perform entity extraction and relation extraction and design graph schemas
- Design and evaluate graph retrieval strategies against a baseline hybrid search pipeline using real-world queries and measurable evaluation metrics
- Improve context quality, enable multi-hop reasoning, and reduce retrieval noise across large document collections
- Take the chosen solution through production implementation and optimize performance and retrieval quality
- Build, train, and evaluate features for LLM applications across design, experimentation, and deployment
- Collaborate with project team and stakeholders to develop MVP and client-focused solutions
- Undertake applied research to address limitations in existing models
- Participate in regular client meetings and prepare presentations and reports on findings and progress
- Produce work potentially publishable to a respected conference or journal
Requirements
- Completion of a graduate level program or higher (M.Sc/Ph.D) in Computing Science, ML or Engineering
- Research or project experience in Natural Language Processing, Knowledge Graphs, and Large Language Models
- Previous experience with LLM use-cases and RAG architectures
- Proficient in Python and related ML frameworks, libraries and toolkits, including Scikit-learn, PyTorch, Pandas, Jupyter, Transformers, HuggingFace Datasets, LangChain, LlamaIndex, Neo4j Python driver, NetworkX, PyTorch Geometric, and spaCy
- Experience with graph-based data structures, knowledge representation, or semantic web technologies
- Familiarity with entity extraction and relation extraction methods and graph databases/libraries
- Must be legally eligible to work in Canada
- Previous experience applying machine learning in NLP, LLMs, and Generative AI projects, including prompt engineering, fine-tuning, or retrieval pipeline optimization
- Hands-on experience in AI/ML development projects
- Publication record in peer-reviewed academic conferences or relevant journals in machine learning
- Desire to take ownership of a problem and demonstrated leadership skills
- Interdisciplinary team player enthusiastic about working together to achieve excellence
- Capable of critical and independent thought
- Able to communicate technical concepts clearly and advise on the application of machine intelligence
- Intellectual curiosity and desire to learn new techniques and technologies
- Industry experience in energy, project engineering, environmental or legal studies is an asset
Benefits
- Paid twelve-month residency
- Work under the mentorship of an Amii Scientist for the duration of the project
- Participate in professional development activities
- Gain access to the Amii community and events
- Build your professional network
- Opportunity for an ongoing machine learning role at the client’s organization at the end of the term, at the client’s discretion
- Disability-related accommodations throughout the recruitment and selection process
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