Alberta Machine Intelligence Institute (Amii)

Machine Learning Resident – Client: Enerva

Alberta Machine Intelligence Institute (Amii)

full-time

Posted on:

Location Type: Hybrid

Location: Edmonton • 🇨🇦 Canada

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Job Level

Mid-LevelSenior

Tech Stack

LinuxPandasPythonPyTorchScikit-LearnTensorflow

About the role

  • This is a paid residency that will be undertaken over a 12-month period with the potential to be hired by our client, Enerva, afterwards (note: at the discretion of the client).
  • The Resident will report to an Amii Scientist and regularly consult with the client team to share insights and engage in knowledge transfer activities.
  • Successful candidates will be members of a cross-functional project team with backgrounds in ML research, project management, software engineering, and new product development.
  • Design, implement, optimize, and evaluate machine learning models to support energy consumption forecasting and related analytical tasks.
  • Prepare, clean, and preprocess high-quality datasets to ensure they are suitable for training or fine-tuning, validating, and comparing forecasting models.
  • Apply state-of-the-art modeling techniques, ML frameworks, tools and open-source libraries to improve model performance, accelerate workflows, and optimize data processing.
  • Undertake applied research on ML and time-series techniques to improve or extend existing forecasting approaches.
  • Contribute to improving ML pipelines with a focus on efficiency, scalability, and real-time processing capabilities.
  • Collaborate with the project team and stakeholders to develop proof-of-concept and MVP-level solutions aligned with the client.
  • Engage in regular client meetings, contributing to presentations and reports on project progress.

Requirements

  • Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in time-series analysis, or energy forecasting applications.
  • Proficient in developing, training, fine-tuning, and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow, including model tuning and performance optimization.
  • Proficient in Python and common ML frameworks, libraries, and toolkits (e.g., Scikit-learn, LMStudio, TensorFlow, PyTorch, OpenCV, Pandas, HuggingFace), including data cleaning, preprocessing, and feature engineering for modeling workflows.
  • Solid understanding of classical statistics and its application in model evaluation, validation, and performance assessment.
  • Familiarity with Linux, Git version control, and writing clean code.
  • A positive attitude towards learning and applying machine learning techniques in a new applied domain.
  • Must be legally eligible to work in Canada.
Benefits
  • 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
  • Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer)
  • Build your professional network
  • The opportunity for an ongoing machine learning role at the client’s organization at the end of the term (at the client’s discretion)

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningdeep neural networkstime-series analysismodel evaluationmodel optimizationdata cleaningfeature engineeringperformance assessmentPythonLinux
Soft skills
collaborationcommunicationknowledge transferpositive attitudeproject management
Certifications
MScPhD