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Machine Learning Resident – Client ModeDi
Alberta Machine Intelligence Institute (Amii). Design, build, and evaluate a secure LLM-based system that streamlines appraisal workflows and supports highest and best use analysis for real estate appraisers .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Natural Language Processing and Machine Learning, with a strong focus on LLM-based systems and retrieval-augmented generation. Proficient in Python and modern AI frameworks, with experience in designing evaluation frameworks and deploying machine learning models in production environments.
Highest-signal resume keywords
Natural Language ProcessingMachine LearningPython ProgrammingRetrieval-Augmented GenerationEvaluation Framework Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Large Language ModelsDocument ParsingConfidence CalibrationBenchmark ConstructionCitation EvaluationUncertainty QuantificationSoftware EngineeringMachine Learning DeploymentClean Code PracticesProject Experience
Soft Skills
Leadership SkillsCritical ThinkingTeam CollaborationCommunication SkillsIntellectual Curiosity
Tools & Technologies
PyTorchHugging FaceTransformersLinuxGitCommercial LLM APIsModel Context ProtocolAgent Orchestration FrameworksPydanticLangGraph
Industry Keywords
Real EstateAppraisalUrban PlanningRegulated DomainAuditabilitySource TraceabilityAccess Control
Tech Stack
Tools & technologiesLinuxPythonPyTorch
About the role
Key responsibilities & impact- Design, build, and evaluate a secure LLM-based system that streamlines appraisal workflows and supports highest and best use analysis for real estate appraisers
- Develop ingestion and retrieval pipelines parsing mixed text and tabular content from municipal planning documents and zoning bylaws
- Build citation-grounded generation and confidence estimation components with traceable source documents for appraisal reports
- Build evaluation infrastructure including expert-annotated benchmarks, citation accuracy and faithfulness scoring, confidence calibration analysis, adversarial and prompt-injection test suites, and CI-gated regression testing
- Implement secure infrastructure with role-based access control restricted to vetted appraisers and auditable system-usage logging
- Conduct applied research in retrieval-augmented generation, document and table understanding, and uncertainty quantification
- Collaborate with the project team and stakeholders to develop MVP and client-focused solutions
- Engage in regular client meetings and contribute to presentations and project-progress reports
- Report to an Amii Scientist and regularly consult with the client team for knowledge transfer
Requirements
What you’ll need- Completion of a Computer Science or related graduate degree program MSc. or PhD with specialization in Natural Language Processing, Machine Learning, Large Language Models, or Applied AI
- Research or project experience with retrieval-augmented generation, document parsing, or LLM-based question answering over long or semi-structured documents
- Proficiency in Python and modern AI frameworks such as PyTorch, Hugging Face, Transformers, vLLM, Unsloth, LangGraph, Pydantic, commercial LLM APIs such as Anthropic and OpenAI, and related machine learning libraries
- Familiarity with Linux, Git version control, and writing clean code
- Positive attitude towards learning and understanding a new applied domain
- Must be legally eligible to work in Canada
- Experience designing evaluation frameworks for LLM or retrieval-augmented systems, including benchmark construction, LLM-as-judge methods, faithfulness and citation evaluation, and offline and online evaluation
- Experience with the Model Context Protocol, agent orchestration frameworks, or durable multi-step workflow systems
- Familiarity with prompt injection, guardrails, and safe handling of untrusted input in production LLM systems
- Experience with uncertainty quantification or confidence calibration for LLM outputs
- Exposure to real estate, appraisal, urban planning, or another regulated domain where auditability, source traceability, and access control are first-class requirements
- Experience deploying machine learning models in production environments or strong software engineering or MLE skills
- Publication record in peer-reviewed academic conferences or relevant journals in ML or Applied AI
- 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
- Ability to communicate technical concepts clearly and advise on applying machine intelligence
- Intellectual curiosity and desire to learn new techniques and technologies
Benefits
Comp & perks- Paid twelve-month residency
- Mentorship by an Amii Scientist for the duration of the project
- Professional development activities
- Access to the Amii community and events
- Paid work at a fair and equitable rate negotiated at the time of offer
- Opportunity for an ongoing machine learning role at the client’s organization at the end of the term, at the client’s discretion
- Professional networking opportunities