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Junior Machine Learning Engineer 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 ...

Faire

Staff Machine Learning Platform Engineer

Kitchener, ON · On-site

CA$216K - CA$297K/yr

About this role As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the ...

Linamar

Process Engineer - Junior

Guelph, ON · On-site

Engineer - Process, Junior Job Summary Work as a trainee process engineer, under guidance of a ... Knowledge of SPC methods, process and machine capability requirements, blueprint reading and ...

BWXT

Manufacturing Engineer, Junior

Cambridge, ON · On-site

Position Overview: As our Manufacturing Engineer, Junior, you will establish and refine ... Develop and support manufacturing procedures across fitting, welding, machining, assembly, and ...

TELUS

AI Lead/Developer

Waterloo, ON

Lead technical design discussions, conduct architecture reviews, and mentor junior developers to ... Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI

Manulife

Lead AI Platform Engineer

Waterloo, ON · Hybrid

Stay updated with the latest advancements in AI and machine learning technologies * Experiment with ... Provide guidance and mentorship to junior engineers and other team members Required Qualifications:

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 ...

Targeted Talent

Data Scientist

Kitchener, ON · On-site

$80K - $100K/yr

We are looking for a Junior to Intermediate Data Scientist for our client. This is a permanent ... Previous experience with Machine Learning, Data Science and solving problems at scale Perks:

Targeted Talent

Data Scientist

Kitchener, ON · On-site

$80K - $100K/yr

We are looking for a Junior to Intermediate Data Scientist for our client. This is a permanent ... Previous experience with Machine Learning, Data Science and solving problems at scale Perks:

Syntronic

Lead Software Developer (AOSP)

Waterloo, ON

CA$140K - CA$170K/yr

We are seeking a Lead Software Engineer to drive the design, development, and maintenance of ... Knowledge of Machine Learning and experience using AI tools in the development process.

Linamar

Application Developer, Junior

Guelph, ON

Job Title: Application Developer, Junior - Finance Systems Job Summary The Junior Application ... Engage in continuous learning through updates in technical skills through technical reading ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Waterloo, ON

Junior Machine Learning Engineer information

See Waterloo, ON salary details

$24.2K

$111.1K

$193.5K

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

As of Jul 13, 2026, the average yearly pay for junior machine learning engineer in Waterloo, ON is $111,098.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,378.00 and $138,921.00 per year, depending on experience, location, and employer.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

A junior machine learning engineer assists in developing, testing, and deploying machine learning models under supervision. They work with data preprocessing, feature engineering, and use tools like Python and libraries such as TensorFlow or scikit-learn to support AI projects. This role often requires foundational knowledge of algorithms, programming, and data analysis.

How much does a junior machine learning engineer make?

A junior machine learning engineer typically earns between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires advanced degrees, specialized certifications, and a strong track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. These positions usually involve leadership, strategic planning, and significant experience, and they tend to be found in large tech companies or specialized AI firms.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

More about Junior Machine Learning Engineer jobs
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 cities near Waterloo, ON are hiring for Junior Machine Learning Engineer jobs? Cities near Waterloo, ON with the most Junior Machine Learning Engineer job openings:
Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Waterloo, ON as of July 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $111,098 per year, or $53.4 per hour.
Machine Learning Engineer, Edge AI

Machine Learning Engineer, Edge AI

onsemi

Waterloo, ON • On-site

CA$120K - CA$170K/yr

Full-time

Re-posted 24 days ago

Onsemi rating

8.3

Company rating: 8.3 out of 10

Based on 19 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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