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Machine Learning Developer Intern Jobs in Ottawa, ON

NavitasPartners

MLOps Engineer (BFSI) - MLEAS

Ottawa, ON · On-site

$30/hr

The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment, monitoring, and governance of AI models. Key Responsibilities: * Build ML deployment ...

NavitasPartners

MLOps Engineer (BFSI) - MLEAS

Ottawa, ON · On-site

CA$30/hr

The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment, monitoring, and governance of AI models. Key Responsibilities: * Build ML deployment ...

Uottawa

APTPUO-Fall 2026-DTI6302 F

Ottawa, ON

CA$239.47/hr

Ecole de conception et d'innovation pedagogique en genie \\ School of Engineering Design and Teaching Innovation Course Title: Machine Learning Operations Course Code: DTI6302 Section: B Course ...

BDO Canada

AI Engineer

Ottawa, ON · On-site

CA$77K - CA$117K/yr

Practical experience with DevOps and MLOps practices, including Docker, Kubernetes, and CI/CD pipelines for machine learning workloads. * Familiarity with machine learning lifecycle and ...

Nokia

Data Science Co-op/Intern

Kanata, ON · Hybrid

... Engineering, or a related field with an accredited school in Canada. * Interest in software ... Interest and experience with Machine Learning and AI. * Experience with data ingestion into a tool ...

DREAM

Intern, Development Accounting

Ottawa, ON

CA$21 - CA$25/hr

We want you on board because you are keen on learning from and working with our dynamic team. In ... We are one of Canada's largest developers, building communities for people to live in; developing ...

Spaceium

AI Engineer

Ottawa, ON

CA$75K - CA$110K/yr

You will work at the intersection of machine learning and space systems, building AI capabilities ... Strong programming skills in Python * Experience with machine learning frameworks (PyTorch ...

TELUS

Staff Applied AI/ML Scientist

Ottawa, ON

Expertise in machine learning frameworks such as TensorFlow, Pytorch, and Keras * Strong understanding of software and AI development lifecycles, with experience in DevOps and MLOps practices

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Machine Learning Developer Intern information

How do Machine Learning Developer Interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a Machine Learning Developer Intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a Machine Learning Developer Intern, and why are they important?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities near Ottawa, ON are hiring for Machine Learning Developer Intern jobs? Cities near Ottawa, ON with the most Machine Learning Developer Intern job openings:
Machine Learning Developer Intern jobs near you

MLOps Engineer (BFSI) - MLEAS

NavitasPartners

Ottawa, ON • On-site

$30/hr

Other

Posted 6 days ago

Job description

Job Title: MLOps Engineer (BFSI)

Position Overview:
The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment, monitoring, and governance of AI models.

Key Responsibilities:

  • Build ML deployment pipelines.
  • Implement CI/CD for machine learning workloads.
  • Automate model retraining and validation.
  • Establish model monitoring and observability.
  • Manage ML infrastructure and environments.
  • Ensure compliance and governance requirements.

Required Skills:

  • MLOps
  • MLflow
  • Kubeflow
  • Docker
  • Kubernetes
  • Python
  • GitHub Actions
  • Azure DevOps
  • Terraform
  • Monitoring Tools

Required Qualifications:

  • Bachelor's degree in Computer Science or related field.
  • 5+ years of MLOps or ML Engineering experience.

Mandatory Industry Experience:

  • Must have prior BFSI experience supporting regulated AI/ML environments, model governance, risk management, fraud analytics, or financial decisioning systems.

For more details reach at resumes@navitassols.com

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