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Machine Learning Engineer Intern Jobs in Waterloo, ON

onsemi

Machine Learning Engineer, Edge AI

Waterloo, ON · On-site

CA$120K - CA$170K/yr

We are looking for a Machine Learning Engineer, Edge AI to lead the integration and control of our next-generation AI accelerators. As our products evolve to include dedicated neural network hardware ...

Dialpad

Applied Scientist

Kitchener, ON · On-site +1

Develop, implement, and refine state-of-the-art Natural Language Processing and Machine Learning ... Collaborate with cross-functional teams, including engineering, product, and design, to effectively ...

Ag

Sr AI/ML Software Developer

Waterloo, ON · Hybrid

As a Senior AI/ML Software Developer, you will enhance core functionality-such as flight scheduling ... Independently own and drive the end-to-end Machine Learning lifecycle (MLOps), from model packaging ...

ATS Automation

Data Scientist

Cambridge, ON · On-site

CA$600/day

Education • A post-secondary engineering degree, diploma or equivalent in a quantitative field (Computer Science, Information system, Mathematic, Statistics, Machine Learning, Artificial ...

Gore Mutual Insurance

Data Scientist

Cambridge, ON · On-site

Support deployment of machine learning models into production environments, including CI/CD workflows and MLOps practices under supervision Create models through advanced data feature engineering

Gore Mutual Insurance

Data Scientist

Cambridge, ON · Hybrid

CA$64K - CA$114K/yr

Support deployment of machine learning models into production environments, including CI/CD workflows and MLOps practices under supervision Create models through advanced data feature engineering

Dialpad

Applied Scientist

Kitchener, ON · On-site +1

Collaboration will be key as you work alongside our engineering, design, and product teams to build ... Demonstrated experience with machine learning, Python, PyTorch, and other relevant tools and ...

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All JobsMachine Learning Engineer Intern JobsMachine Learning Engineer Intern Jobs in Waterloo, ON

Machine Learning Engineer Intern information

See Waterloo, ON salary details

$21.4K

$112.6K

$200.9K

How much do machine learning engineer intern jobs pay per year?

As of Jul 26, 2026, the average yearly pay for machine learning engineer intern in Waterloo, ON is $112,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,002.00 and $152,907.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

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

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in Waterloo, ON? The most popular types of Machine Learning Engineer jobs in Waterloo, ON are:
What job categories do people searching Machine Learning Engineer Intern jobs in Waterloo, ON look for? The top searched job categories for Machine Learning Engineer Intern jobs in Waterloo, ON are:
What cities near Waterloo, ON are hiring for Machine Learning Engineer Intern jobs? Cities near Waterloo, ON with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Waterloo, ON as of July 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $112,573 per year, or $54.1 per hour.
Machine Learning Engineer, Edge AI

Machine Learning Engineer, Edge AI

onsemi

Waterloo, ON • On-site

CA$120K - CA$170K/yr

Full-time

Posted 7 days ago

Onsemi rating

8.3

Company rating: 8.3 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

Job description

We are looking for a Machine Learning Engineer, Edge AI to lead the integration and control of our next-generation AI accelerators. As our products evolve to include dedicated neural network hardware, the challenge shifts from pure algorithm implementation to complex hardware orchestration.

This role is about more than just writing kernels; it's about defining the firmware layer that sits between high-level AI frameworks and our custom silicon. You will be responsible for how our DSPs manage, schedule, and feed data to these accelerators. We need a veteran who can look at a PyTorch model and determine the best way to tile memory, manage DMA transfers, and synchronize processing to ensure we hit our ultra-low-power targets while maximizing throughput. You will also be the primary technical voice influencing our future hardware specs to ensure our accelerators are actually "firmware-friendly."

onsemi (Nasdaq: ON) is driving disruptive innovations to help build a better future. With a focus on automotive and industrial end-markets, the company is accelerating change in megatrends such as vehicle electrification and safety, sustainable energy grids, industrial automation, and 5G and cloud infrastructure. With a highly differentiated and innovative product portfolio, onsemi creates intelligent power and sensing technologies that solve the world's most complex challenges and leads the way in creating a safer, cleaner, and smarter world.

More details about our company benefits can be found here:

https://www.onsemi.com/careers/career-benefits

We are committed to sourcing, attracting, and hiring high-performance innovators, while providing all candidates a positive recruitment experience that builds our brand as a great place to work.


onsemi is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, ancestry, national origin, age, marital status, pregnancy, sex, sexual orientation, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, or any other protected category under applicable federal, state, or local laws.

If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact Talent.acquisition@onsemi.com for assistance.

What You'll Need

  • Strong Python, PyTorch and ONNX experience developing, training, evaluating, and deploying machine learning models.
  • Deep understanding of modern AI architectures including CNNs, Transformers, state-space models, and other emerging neural network approaches.
  • Experience optimizing, deploying and debugging models across a wide spectrum of edge devices, from ultra-constrained microcontrollers and DSPs to high-performance AI accelerators and GPUs.
  • Experience developing machine learning solutions for one or more sensing domains, including time-series signals, audio, computer vision, or ultrasonic sensing.
  • Hands-on experience with model compression and deployment techniques such as quantization, pruning, graph optimization, and operator/kernel optimization.
  • Practical experience translating research concepts into production-quality systems.
  • Strong understanding of model performance tradeoffs involving latency, memory footprint, power consumption, and accuracy.
  • 4+ years of industry and/or academic experience in machine learning research, model development, or AI systems engineering.

Nice to Have

  • CUDA development and GPU optimization experience.
  • Experience with TensorRT, ONNX Runtime, TVN, IREE, or similar inference frameworks.
  • Experience with TinyML, embedded inference runtimes, or DSP programming.
  • Familiarity with multimodal AI systems.

onsemi is excited to share the base salary range for this position i$120,000 - $170,000 exclusive of fringe benefits or potential bonuses.The final pay rate for the successful candidate will depend on geographic location, skills, education, experience, and/or consideration of internal equity of our current team members. We also offer a competitive benefits package

What You Will Do

  • Lead research and development efforts in edge AI and embedded machine learning.
  • Design, train, evaluate, optimize, and deploy machine learning models spanning applications from low-power 1D sensor processing through high-dimensional sensing systems such as ultrasonic arrays.
  • Investigate and develop novel architectures for constrained edge deployments, balancing performance, power, latency, and memory requirements.
  • Optimize AI workloads through techniques such as quantization, pruning, graph optimization, kernel acceleration, and hardware-aware training.
  • Deploy models across a variety of hardware platforms, including onsemi solutions and third-party edge AI hardware.
  • Stay current with advances in machine learning research and translate promising techniques into scalable, production-ready products.
  • Work closely with hardware, firmware, and software teams to co-design AI solutions that maximize efficiency, performance, and scalability on resource-constrained edge platforms

What Onsemi employees say

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