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Entry Level Machine Learning Engineer Jobs in Saskatchewan

Brandt

Design Engineer

Regina, SK

The engineer is expected to engage in continuous learning and improvement in both professional ... Designing Hydraulic systems, machines, and devices which meet our customer's needs and which, when ...

Brandt

Territory Manager

Regina, SK

Prepare customer quotations and proposals in collaboration with engineering, estimating, and ... Continuous Learning: through on-the-job training and educational opportunities. * Opportunities for ...

Brandt

Territory Manager - Construction

Regina, SK

We provide industry leading technologies to the construction, building, surveying, engineering ... Understand and apply Machine and Company Feature, Advantage, Benefit statements to drive sales ...

Weyerhaeuser

HED/GE Operations Area Manager

Regina, SK

CA$95K - CA$139K/yr

... Engineering. Annual production is 540mm3/8. The workforce of Approximately 160 employees is ... Personally, does final qualification learning checks on tasks and Job Instructions. * Leads ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Saskatchewan

Entry Level Machine Learning Engineer information

See Saskatchewan salary details

$21K

$87.2K

$186K

How much do entry level machine learning engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for entry level machine learning engineer in Saskatchewan is $87,195.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What job categories do people searching Entry Level Machine Learning Engineer jobs in Saskatchewan look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Saskatchewan are:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Saskatchewan as of July 2026, with employment types broken down into 1% Locum Tenens, 94% Full Time, 3% Part Time, and 2% Contract. Highlights an 79% Physical, 4% Hybrid, and 17% Remote job distribution, with an average salary of $87,195 per year, or $41.9 per hour.

Postdoctoral Fellow, Plant Sciences

American Institute for Chemical Engineers

Saskatoon, SK • Remote

Other

Re-posted 5 days ago

Job description

Primary Purpose: The Agronomic Crop Imaging Lab (ACI Lab), University of Saskatchewan invites applications for a three-year postdoctoral fellowship (PDF) under its Research Grant Programs. The selected candidate will contribute to a number of ongoing research projects.

Nature of Work: Combination of desk and fieldwork

Accountabilities: The PDF will play a key role in connecting a dynamic team of soil and crop scientists, GIS specialists, remote sensing experts, and computer programmers. They will be responsible for:

  • Conducting fieldwork using UAVs (drones) to capture high-resolution imagery and environmental data
  • Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors
  • Leveraging artificial intelligence, e.g. machine learning, reinforcement learning to develop data-driven, space-time explicit precision agronomic solutions
  • Utilizing high-performance computing (HPC) systems for large-scale geospatial data processing, model training, and validation
  • Designing and managing scalable ETL (Extract, Transform, Load) pipelines to integrate multi-source, multimodal datasets
  • Applying big-data analytic, including spatio-temporal modeling and deep learning techniques
  • Collaborating with an interdisciplinary team of soil scientists, agronomists, and computer scientists
  • Presenting research findings at national and international conferences and contributing to peer-reviewed publications
  • Being part of the new Nutrien Centre for Digital and Sustainable Agriculture

Education: Ph.D. in Plant Science, Environmental Science, Soil Science, Geography, Bioresources, Computer Science, or related discipline

Licenses: A valid class 5 driver's license is a necessity.

Experience: The candidate should have extensive experience in handling big geospatial datasets, remote sensing, and quantitative research techniques. Strong scientific communication and writing skills are essential. Additionally, the candidate must demonstrate the ability to work independently while collaborating effectively within a team.

Skills: Expertise in varying disciplines, with strong proficiency in programming languages such as R, Python or Javascript is required. Experience in big data analytics and deep learning using time series analysis and spatial interpolation of landscape features in the Canadian Prairie would be considered an asset.

To Apply:
All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority. The University of Saskatchewan is committed to the principles of employment equity. The University encourages applications from qualified Aboriginal people, persons with a disability, racially visible persons, and women.

Please include your curriculum vitae, cover letter, academic transcripts, degree certificate(s), and contact information in your application.

Apply