Machine Learning Specialist at Primary Engineering and Construction
Calgary, AB, Canada -
Full Time


Start Date

Immediate

Expiry Date

04 Jul, 25

Salary

0.0

Posted On

21 Jun, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Communication Skills, Python, Ml, Analytical Skills, Computer Science, Academic Research

Industry

Information Technology/IT

Description

Location: Calgary
Reports to: IT Systems Administrator
Job Posting#: 113
Application Deadline: July 4, 2025
Reporting to the IT Systems Administrator, the Machine Learning Specialist is responsible for taking the lead in the exploration and development of various AI-based use cases within the organization. This role is central to Primary’s digital transformation strategy, leveraging data science and AI to drive innovation, enhance operational efficiency, and uncover new insights across the enterprise.

ABOUT US

Primary Engineering and Construction Corporation (Primary) is a growth-oriented industry leader providing professional electrical engineering and construction services and specializing in emerging marketplaces in Alberta, British Columbia, Manitoba, Ontario and Saskatchewan.
We offer design and design/build services for all types of electric utility distribution infrastructure to a wide variety of clients including electric utility companies, developers, builders, commercial and industrial businesses, oil companies, government, and private contractors. Our devotion to excellence has attracted some of the best young professional minds to our company.
Primary is the proud recipient of EHRC’s Workplace Culture Innovator Award, recognizing our commitment to fostering a health, inclusive, and positive work environment.
Primary is recognized
by The Career Directory
for excellence in graduate recruitment.

Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • 2–3 years of hands-on experience developing and deploying machine learning models in real-world applications — or equivalent experience through academic research, startups, or open-source contributions.
  • Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
  • Strong analytical skills and experience working with large and diverse datasets.
  • Excellent communication skills and the ability to explain complex concepts to non-technical stakeholders
Responsibilities
  • Lead the end-to-end lifecycle of AI/ML projects: from ideation and data acquisition to model training, evaluation, deployment, and monitoring.
  • Collaborate with cross-functional teams (engineering, operations, safety, finance) to identify and prioritize high-impact AI use cases.
  • Develop and deploy machine learning models to address real-world challenges in areas such as project planning, safety analytics, equipment maintenance, quality control, or logistics optimization.
  • Collect, clean, and analyze large datasets from various internal systems and sources (e.g., HRIS systems, Technical Datasets, ERP systems).
  • Build proof-of-concept solutions to validate ideas and support business cases for broader implementation.
  • Partner with internal and external support to integrate models into production environments where appropriate.
  • Stay current with advancements in AI/ML and assess their applicability within the engineering and construction context.
  • Lead Company-wide AI Training and Upskilling Initiatives
  • Contribute to a culture of innovation by sharing knowledge, mentoring peers, and fostering experimentation.
  • Help define and shape an AI/MI roadmap that aligns with Primary’s strategic objectives.

Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • 2–3 years of hands-on experience developing and deploying machine learning models in real-world applications — or equivalent experience through academic research, startups, or open-source contributions.
  • Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
  • Strong analytical skills and experience working with large and diverse datasets.
  • Excellent communication skills and the ability to explain complex concepts to non-technical stakeholders.
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