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Machine Learning Analyst

  1. Mississauga
  2. Nuclear
R-116681

Machine Learning Analyst

AtkinsRéalis is one of Canada's largest private sector nuclear engineering groups. We have been providing a wide range of services to the nuclear industry in Canada and around the world since for more than 60 years. We are proud to be the steward of Canadian CANDU nuclear technology.

Reporting to the Digital Solutions Manager, the Machine Learning Engineer will develop applications using a wide range of machine learning techniques, algorithms and tools to extract tangible value from Nuclear plant asset and operational data. She / he will have a baseline level of proficiency in Data Science and will lead data collection, curation, and preprocessing, to training models and deploying them to production.

Location - Mississauga, ON

Your role within the team:

  • Develop, Deploy and Maintain Data Solutions leveraging ML algorithms.
  • Ensure high levels of data quality through the development and production lifecycles.
  • Seek and obtain the required data sets from multiple sources.
  • Define data validation strategies.
  • Perform Feature Engineering for datasets.
  • Train models to the desired level of prediction accuracy.
  • Analyzing the errors of the model and designing strategies to overcome them.
  • Deploying models to production through a continuous delivery mechanism in an Agile DevOps environment.

Why choose AtkinsRéalis as an employer?

Because we offer:

  • The opportunity to work on various major projects for internal and external clients.
  • An exciting environment where work-life balance is important.
  • A wide array of learning and development opportunities.
  • Competitive pay, flexible benefits, an employee share plan, and a defined contribution pension plan.
  • A work environment focused on health and safety.

The ideal candidate:

  • Bachelor’s degree in Engineering or Honours degree in Computer Science, Information Systems, or similar program, with specialization in AI / ML.
  • 1- 2 years of ML development and deployment experience in an industrial setting; Nuclear experience is an asset.
  • Experience in Project Management is an asset.
  • Competence in building complex models and some history of innovation is key.
  • Proficient in Data Science / Advanced Analytics / Machine Learning key principles.
  • Experience with concrete inspection or crack detection is an asset.
  • Experience in collaborating with multi discipline teams to develop ML solutions in a cloud based environment.
  • Solid understanding of data science, and the ability to relate data to value delivery.
  • Experience in SaaS / XaaS delivery models.
  • Experience in managing app development projects in a mature DevOps environment.

Are you up for this challenge? Apply today and join our team to help engineer a Better Future for our Planet and its People.

At AtkinsRéalis, we seek to hire individuals with diverse characteristics, backgrounds, and perspectives. We strongly believe that world-class talent makes no distinctions based on gender, ethnic or national origin, sexual identity and orientation, age, religion, or disability, but enriches itself through these differences.  
 

AtkinsRéalis cares about your privacy. AtkinsRéalis and other subsidiary or affiliated companies of AtkinsRéalis (referred to throughout as “AtkinsRéalis”) are committed to protecting your privacy. Please consult our Privacy Notice on our Careers site to know more about how we collect, use, and transfer your Personal Data.
 

By submitting your personal information to AtkinsRéalis, you confirm that you have read and accept our Privacy Notice.

Appropriate accommodations will be provided upon request throughout the recruitment and hiring process as required by Company policy and the Accessibility for Ontarians with Disabilities Act (AODA).

Successful applicants will be notified about AtkinsRéalis’ accommodation policies at the time the employment offer is extended, and the information will be shared with new personnel during the onboarding process.

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Preview

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Content type

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Publish date

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Summary

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