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Fall Machine Learning Co Op Jobs in Ottawa, ON (NOW HIRING)

Thales

Naval Architect Co-op

Ottawa, ON · Hybrid

Naval Architect Intern - Fall 2026 & Winter 2027 - Hybrid - Full-Time - 4-12 months Victoria, BC ... May be required to undertake inspections in machinery spaces of Naval ships involving bending and ...

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Fall Machine Learning Co Op information

What is a Fall Machine Learning Co Op?

A Fall Machine Learning Co-Op is a temporary, typically full-time position for students or recent graduates to gain hands-on experience in applying machine learning techniques. These roles usually involve working with data, training models, and optimizing algorithms under the supervision of experienced engineers or researchers. They are offered during the fall semester and can last several months. Companies use these positions to provide practical learning opportunities and assess potential future hires.

What can I expect from the day-to-day experience of a Fall Machine Learning Co Op?

As a Fall Machine Learning Co Op, you'll typically work with a team of data scientists and engineers on real projects that may involve data cleaning, model development, testing, and reporting insights. Your days might include collaborating in meetings, coding, analyzing data, and presenting findings to team members or supervisors. You'll receive mentorship from experienced professionals and have opportunities to participate in code reviews and brainstorming sessions. This structure helps you build technical skills, broaden your professional network, and gain a comprehensive understanding of how machine learning is applied in a business setting.

What are the key skills and qualifications needed to thrive in the Fall Machine Learning Co Op position, and why are they important?

To thrive as a Fall Machine Learning Co Op, you should have a solid background in programming (especially Python), statistics, and machine learning concepts, often supported by coursework or hands-on projects in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, and data analysis libraries such as pandas and scikit-learn is highly valued, while certifications in AI or data science can be a plus. Strong problem-solving skills, eagerness to learn, effective communication, and teamwork help you stand out in this role. These skills are crucial for contributing to real-world projects, collaborating with technical teams, and gaining valuable experience in a fast-paced, innovation-driven environment.

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For Fall Machine Learning Co Op jobs in Ottawa, ON, the most frequently searched job titles are:

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Cities near Ottawa, ON with the most Fall Machine Learning Co Op job openings:

Fall Machine Learning Co Op jobs near you
Infographic showing various Fall Machine Learning Co Op job openings in Ottawa, ON as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

User Terminal Engineering Co-op (Fall 2026)

Telesat

Ottawa, ON • On-site

Full-time

Posted 29 days ago

Job description

Telesat (Nasdaq and TSX: TSAT) is a leading global satellite operator, providing reliable and secure satellite-delivered communications solutions worldwide to broadcast, telecommunications, corporate and government customers for over 55 years.  Backed by a legacy of engineering excellence, reliability and industry-leading customer service, Telesat has grown to be one of the largest and most successful global satellite operators.

Telesat Lightspeed, our revolutionary Low Earth Orbit (LEO) satellite network, scheduled to begin service in 2027, will revolutionize global broadband connectivity for enterprise and Government users by delivering a combination of high capacity, security, resiliency and affordability with ultra-low latency and fiber-like speeds. Telesat is headquartered in Ottawa, Canada, and has offices and facilities around the world.
The company's state-of-the-art Satellite fleet consists of 12 GEO satellites, the Canadian payload on ViaSat-1 and one LEO 3 demonstration satellite.  For more information, follow Telesat on X and LinkedIn or visit www.telesat.com


Under the guidance of technical staff, the User Terminal Engineering Coop will support the design and testing of User Terminal. The role may focus on SW development tasks for the User Terminal sub-systems.
Main Responsibilities
  • Support User Terminal design and test activities
  • Perform theoretical analysis
  • Support SW Development in Python, C++, or other assigned languages
  • Develop test and automation scripts
  • Collect and analyze test and/or simulation results
  • Generate reports presenting test plans, results and conclusions
  • Develop and execute lab setups, test plans, and test procedures
  • Support User Terminal team in developing and maintaining documentation for User Terminal sub-systems
  • At the end of the co-op - present the work, analysis and findings to the User Terminal Segment Management 
Education & Experience Required
  • University student in their 2nd or 3rd year working towards a Bachelor's degree in technical or engineering field with an interest in Satellite Communications, antenna and modem designs, RF equipment including low noise amplifiers (LNAs), power amplifiers, up/down converters, etc.
  • Familiarity with wireless transmission techniques and modulation
  • Awareness of satellite communication technologies
  • Good communicator in a hybrid work environment
  • Written and verbal skills in English
At Telesat, we take pride in being an equal opportunity employer that values equality in the workplace.   We are committed to providing the best candidate experience possible including any required accommodations at every stage of our interview process.   All qualified applicants that have been selected for an interview that require accommodations, are advised to inform the Telesat Talent team accordingly.  We will work with you to meet your needs.   All accommodation information provided will be treated as confidential.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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