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Summary

Join Jotson as a Machine Learning Resident to develop innovative ML/DL solutions for detecting anomalies in energy consumption patterns over a 12-month paid residency with potential for permanent placement.

Key Responsibilities: Clean and preprocess energy datasets, conduct exploratory data analysis, design and train ML/DL models, develop data workflows, and collaborate with stakeholders to create client-centric solutions for anomaly detection in household and business energy usage.
Skills & Tools: Solid knowledge of machine learning, experience with time series data, proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn), and understanding of deep learning techniques including RNNs, LSTMs, GRUs, and Transformers.
Qualifications: Completion of a Computing Science or ML graduate program (MSc or Ph.D) with research or project experience in time series models (ARIMA, Facebook Prophet) and deep learning applications for sequence modeling.
Location: Hybrid in Edmonton, Alberta, Canada (with relocation to Calgary required if converted to permanent role with client)
Compensation: CA$60,000 – CA$90,000/year

Job Description

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Fast Facts

Join Jotson as a Machine Learning Resident to tackle time-series problems in energy data, collaborating with experts to develop innovative ML/DL solutions for anomaly detection in energy consumption.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Responsibilities: Key responsibilities include cleaning datasets, conducting data analysis, designing ML/DL models, developing workflows, and collaborating on client-centric solutions.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Skills: Required skills include knowledge of machine learning, experience with time series data, proficiency in Python and related ML frameworks, and a positive attitude toward learning.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Qualifications: Preferred qualifications include a graduate degree in Computing Science or ML, experience with time-series models and deep learning techniques, and familiarity with anomaly detection methods.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Location: The position is based in Edmonton, Alberta, Canada, with a preference for local candidates.

liETtVLaARqgmMEbYzHNNLIzUPcdfPrwhYtVK7Qa.png Compensation: Not provided by employer. Typical compensation ranges for this position are between CAD 60,000 - CAD 90,000.



“Join us for a unique ML Resident role tackling time-series problems in the energy domain with ML/DL. You’ll collaborate with a dynamic and fast-paced team of machine learning scientists and domain experts, developing innovative models and products with energy data.” 

- Maithrreye Srinivasan, Machine Learning Scientist and Dave Staszak, Lead Machine Learning Scientist

About the Role

This is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client afterwards (note: at the discretion of the client and with the requirement of being located in Calgary at that time). The resident will be reporting to an Amii Machine Learning Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities.

About our Client

Jotson's mission is to help Canadians become informed and confident in making energy-related decisions. They achieve this by making household energy data easy to access, track, and understand. The company has decades of experience working in the energy industry and looks to apply its knowledge to bridge the gap between the energy sector and the everyday consumer.

About the Project 

Jotson aims to develop a machine-learning solution for detecting anomalies in energy consumption patterns for household and business properties. This solution will alert consumers when energy consumption or charges deviate from expected patterns. Anomaly detection plays a crucial role in monitoring and managing energy usage by flagging unusual consumption patterns or outliers. Anomalies may indicate:

  • Equipment inefficiencies or failures.
  • Opportunities to detect energy inefficiencies early and take corrective action.
  • Misaligned energy systems or operational issues.
  • Opportunities for energy savings or optimization.
  • Inaccurate metering/billing that can lead to financial losses.

Required Skills / Expertise

We’re looking for a talented and enthusiastic individual with solid knowledge of machine learning and experience working with time series data.

Key Responsibilities:

  • Clean, preprocess, and curate historical energy usage datasets.
  • Conduct exploratory data analysis to identify patterns and anomalies.
  • Design, build, train, and evaluate ML/DL models
  • Develop data and ML workflows
  • Undertake applied research on ML techniques to address the limitations in existing models and develop new approaches
  • Collaborate with project team and stakeholders to develop minimum viable products (MVPs) and client-centric solutions  

Required Qualifications: 

  • Completion of a Computing Science or ML graduate program, MSc. or Ph.D
  • Research or project experience working with time series data and classical time series models (ARIMA, Facebook Prophet, etc.)
  • Solid understanding and experience in applications of deep learning techniques such as sequence models (RNNs, LSTMs, GRUs, Transformers, etc.) or multi task learning
  • Proficient in Python programming language and related ML frameworks, libraries and toolkits (e.g. Scikit learn, Keras, Tensorflow, Pandas, Jupyter notebooks)
  • A positive attitude towards learning and understanding a new applied domain 
  • Must be legally eligible to work in Canada

Preferred Qualifications:

  • Publication record in peer-reviewed academic conferences or relevant journals in machine learning
  • Familiarity with time series anomaly detection methods 
  • Experience/familiarity with software engineering best practices  
  • Experience using cloud platforms (GCP, AWS, Azure, etc.)

Non-Technical Requirements: 

  • 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 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 Lead Scientist for the duration of the project
  • Participate in professional development activities
  • Gain access to the Amii community and events
  • Build your professional network
  • The opportunity for a permanent machine learning role at the client’s organization at the end of the term (at the client’s discretion)

Location

Preference for Calgary or Edmonton

About Amii

One of Canada’s 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 world’s 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 you've been waiting for, please don’t wait for the closing February 24, 2025 to apply - we’re 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 you'd be a fit for Amii. In 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 won’t be used in the selection process.