Machine Learning Resident – Client: Ultimarii

Alberta Machine Intelligence Institute (Amii)

. Report to an Amii Scientist and regularly consult with the Client team .

Posted 10/30/2026full-timeEdmonton • CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Natural Language Processing, Knowledge Graphs, and Large Language Models, with a strong focus on graph retrieval strategies and entity extraction. Proven ability to collaborate effectively with interdisciplinary teams and communicate complex technical concepts.

Highest-signal resume keywords

Natural Language ProcessingKnowledge GraphsLarge Language ModelsPython ProgrammingGraph-Based Data Structures

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Entity ExtractionRelation ExtractionGraph Schema DesignMachine LearningPrompt EngineeringFine-TuningRetrieval Pipeline OptimizationEvaluation MetricsMulti-Hop ReasoningPerformance Optimization

Soft Skills

LeadershipCritical ThinkingCommunicationTeam CollaborationIntellectual Curiosity

Tools & Technologies

Scikit-LearnPyTorchPandasJupyterTransformersHuggingFace DatasetsLangChainLlamaIndexNeo4j Python DriverNetworkX

Industry Keywords

EnergyProject EngineeringEnvironmental StudiesLegal Studies

Tech Stack

Tools & technologies

Neo4jPandasPythonPyTorchScikit-Learn

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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