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Machine Learning Developer 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 ...

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 ...

TELUS

AI Lead/Developer

Waterloo, ON · On-site

... generation of AI engineers, and transform finance operations. Join our team and what we'll ... Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI

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 ...

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

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

Machine Learning Engineer, Edge AI

onsemi

Waterloo, ON • On-site

CA$120K - CA$170K/yr

Full-time

Re-posted 11 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

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