Machine Learning Resident Client Enerva (1 year term)

If you are interested in the application of artificial intelligence (AI) and machine learning (ML) methods for energy consumption modeling and forecasting this is the right opportunity for you. Be a part of the team of research and machine learning scientists building a state-of-the-art predictive model from the ground up and get mentored by some of the best minds in AI during the process.

-Mara Cairo Product Owner Advanced Technology

Description

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. This is a rare opportunity to be mentored by world-class scientists and to develop something truly impactful.

About the Client

Enerva Energy Solutions is a 100% Canadian employee-owned energy efficiency and decarbonization firm dedicated to the mission of optimizing energy costs and reducing global emissions. As the largest Canadian-owned program delivery company in our sector we provide a homegrown alternative to American private equity-backed firms. Our team of 50 engineers analysts and software developers delivers end-to-end energy programs nationwide. At Enerva we dont just consultwe deliver the technical solutions and innovative strategies needed to power a greener more resilient future.

About the Project

This project builds on prior validation work exploring how data-driven approaches can improve the way organizations understand and forecast energy consumption across diverse facilities. The goal is to enhance existing methods used to track plan and manage energy use by developing more adaptable and forward-looking analytical tools that reflect real-world operational conditions.

Working alongside an experienced industry partner the project will focus on learning from historical facility data to identify patterns trends and drivers of energy use over time. Rather than relying on a single predefined solution the work is exploratory and iterative allowing insights from the data to inform direction as the project progresses. Emphasis is placed on producing practical interpretable outcomes that can support budgeting performance tracking and proactive energy management across different facility types.

Required Skills / Expertise

Are you passionate about building great solutions Youll be presented with opportunities to both personally and professionally develop as you build your career. Were looking for a talented and enthusiastic individual with a solid background in machine learning specifically time-series analysis and forecasting.

Key Responsibilities:

• 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.

Required Qualifications:

• 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.

Preferred Qualifications:

• Familiarity with and hands-on experience with time-series or energy consumption data.
• Publication record in peer-reviewed academic conferences or relevant journals in machine learning.
• Experience/familiarity with software engineering best practices in an applied or research setting.
• Experience with deploying machine learning models in production environments or strong software engineering (or MLE) skills is a plus.

Non-Technical Requirements:

• Desire to take ownership of a problem and demonstrate 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 the desire to learn new things techniques and technologies.

Why You Should Apply

Besides gaining industry experience additional perks include:

• 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 clients organization at the end of the term (at the clients discretion)

About Amii

One of Canadas three main institutes for artificial intelligence (AI) and machine learning our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions) training some of the worlds top scientific talent. Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

How to Apply

If this sounds like the opportunity youve been waiting for please dont wait for the closing January 2 2026 to apply - were excited to add a new member to the Amii team for this role and the posting may come down sooner than the closing date if we find the right candidate before the posting closes! When sending your application please send your resume and cover letter indicating why you think youd be a fit for your cover letter please include one professional accomplishment you are most proud of and why.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity religion gender identity sexual orientation age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and wont be used in the selection process.