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Machine Learning Intern Jobs in Ottawa, ON (NOW HIRING)

Nokia

Optical Test Coop/Intern

Kanata, ON · On-site

Optical Test Coop/Intern Number of Position(s): 1 Duration : 12 Months Date : September 8 thto ... A learning environment that fosters both personal growth and professional development - for your ...

Ciena

Resourcing and Enablement Intern

Ottawa, ON

CA$20.50 - CA$27.50/hr

As the global leader in high-speed connectivity, Ciena is committed to a people-first approach. Our teams enjoy a culture focused on prioritizing a flexible work environment that empowers individual ...

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Machine Learning Intern information

What are the key skills and qualifications needed to thrive as a machine learning intern, and why are they important?

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

More about Machine Learning Intern jobs
What are popular job titles related to Machine Learning Intern jobs in Ottawa, ON? For Machine Learning Intern jobs in Ottawa, ON, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern jobs in Ottawa, ON look for? The top searched job categories for Machine Learning Intern jobs in Ottawa, ON are:
What cities near Ottawa, ON are hiring for Machine Learning Intern jobs? Cities near Ottawa, ON with the most Machine Learning Intern job openings:
Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Ottawa, ON as of August 2026, with employment types broken down into 14% Internship, 28% Full Time, 29% Part Time, and 29% Temporary. Highlights an 100% In-person job distribution.

Jr. Deep Packet Inspection QA Engineer

Nokia

Kanata, ON • On-site

Full-time

Posted 13 days ago

Nokia rating

7.9

Company rating: 7.9 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

30th of 97 rated telecommunications companies

Job description

Join a highperformance engineering group working at the forefront of application identification and DDoS mitigation technologies. This role offers a challenging environment where you will analyze complex network behaviors, build automated test systems, and help strengthen technologies protecting global networks.
 

You have:
  • A master's degree or a bachelor's degree in Electrical Engineering, Computer Engineering, Software Engineering, Computer Science, or a related field from an accredited Canadian institution, with graduation in 2025 or expected in Spring 2026.
  • Hands-on experience with Linux-based systems.
  • Strong understanding of computer networking protocols, including:  TCP/IP, DHCP, ARP, DNS
  • Python proficiency (essential) for automation, test development, and debugging.
  • Solid software development skills:
    • Scripting and programming (Python required)
    • Debugging and troubleshooting
    • Experience with Git or similar source control systems
  • A qualitydriven, detailoriented problemsolver who breaks down complex challenges analytically, coupled with a fastlearning, selfstarter mindset that takes ownership and drives work forward independently.
     
It would be nice if you also had:
  • Experience with Wireshark or similar trafficanalysis tools, with exposure to machine learning concepts, data labeling, or trafficclassification models, is considered an asset (but not required).
  • Previous Nokia intern or co-op experience.
  • Contribute to the design, validation, and continuous improvement of application identification algorithms and DDoS mitigation technologies.
  • Verify and analyze application detection mechanisms along with network behaviors involving QUIC, HTTPS, RTP and other protocols.
  • Develop automated test cases in a Linuxbased regression environment to validate application signatures and new DDoS mitigation features.
  • Set up and configure test servers/services (e.g., HTTP servers, DNS servers) to create realistic test environments.
  • Work collaboratively with testers and developers to identify, analyze, report, and resolve software defects.
  • Monitor and debug automated regression systems, improving test coverage and tool capabilities.
  • Break down complex problems piece by piece, diving deep into traffic flows, signatures, packet behavior, and system interactions.
  • Gain hands-on experience in advanced networking, cybersecurity, traffic classification, and largescale mitigation systems.

What Nokia employees say

Hours and flexibility

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