1

Junior Machine Learning Engineer Jobs in Waterloo, ON

The Team The Security Machine Learning Engineer will play a key role in transforming our Security Operations Center (SOC) from reactive to proactive by integrating advanced machine learning and data ...

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 ...

Engineer - Project, Junior Job Summary As a Junior Project Engineer, you will support the execution ... Practical knowledge of cutting tools, machining processes, materials & equipment. What Linamar Has ...

Mentor and review work of junior team members and coop students. Provide shopfloor support and ... Knowledge of CSA machine guarding requirements. Experience with Statistical Process Control (SPC ...

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 ...

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 ...

Position Summary We are seeking an Engineering Co-op Student to support manufacturing, test, and ... Experience with machine learning, computer vision, or image processing. * Familiarity with data ...

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

next page

Showing results 1-20

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 Aug 25, 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 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.

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 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 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.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn 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 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 are popular job titles related to Junior Machine Learning Engineer jobs in Waterloo, ON?

For Junior Machine Learning Engineer jobs in Waterloo, ON, the most frequently searched job titles 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:

Infographic showing various Junior Machine Learning Engineer job openings in Waterloo, ON as of August 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Nights. Highlights an 72% In-person, 16% Hybrid, and 12% Remote job distribution, with an average salary of $111,098 per year, or $53.4 per hour.

Senior Machine Learning Engineer (SOC)

Paris, ON • On-site

Proton
Software Development • 51 - 200 employees

Full-time

Medical, Retirement

Re-posted 7 days ago


Job description

Join Proton and build a better internet where privacy is the default

At Proton, we believe that privacy is a fundamental human right and the cornerstone of democracy. Since our inception in 2014, founded by a team of scientists from CERN, we have dedicated ourselves to providing free and open-source technology to millions worldwide, ensuring access to privacy, security, and freedom online.

Our journey began with Proton Mail, the largest secure email service globally, and has since expanded to include Proton VPN, Proton Calendar, Proton Drive, and Proton Pass. These tools empower individuals and organizations to take control of their personal data, break away from Big Tech's invasive practices, and defeat censorship. Our work impacts hundreds of millions of lives, from activists on the front lines defending freedom to leaders in governments protecting sensitive information. In some cases, Proton's services have even been instrumental in saving lives by enabling secure and private communications in high-risk situations.

Proton is a profitable company that does not rely upon VC funding, supporting over 100 million user accounts with a growing team of over 500 people from over 50 different countries, from the world's top companies and universities. We value intelligence, learning potential, and ambition in our hiring process. Adaptability is key as we navigate uncharted territories and redefine how business is conducted online.

Hiring at Proton is highly selective, with less than 1% of candidates hired. We believe smaller teams of exceptional talent will always prevail over larger teams with lower talent density. You will have the opportunity work with many of the world's top minds in their fields, ranging from former international math and science olympiad winners to chess champions.

We have a global mindset and big ambitions but remain a start-up at heart. We value empowerment and flexibility and keep our structure flat to keep moving fast and avoid unnecessary politics. Tired of blending into the crowd? Join us and do work you can truly be proud of. Check our open-source projects here!

The Team

The Security Machine Learning Engineer will play a key role in transforming our Security Operations Center (SOC) from reactive to proactive by integrating advanced machine learning and data-driven approaches into our detection and response workflows.

This role bridges traditional cybersecurity operations and modern ML-driven analytics, enabling our team to automatically identify emerging threats, anomalous behaviour, and new attack patterns at scale. As a secondary focus, the role could also leverage LLMs and AI engineering to automate analyst workflows and reduce operational toil.

The engineer will sit directly within the security team, ensuring that the solutions built are operationally relevant, and aligned with our security priorities, while also working closely with the internal Machine Learning team (MSA) to leverage their expertise and best practices.

What you will do:

  • ML-Driven Detection & Automation

    • Design, develop, and deploy machine learning models to enhance security detection, anomaly identification, and incident response.
    • Integrate ML outputs into the SOC workflow to enable smarter and faster triage.
    • Continuously evaluate and tune models to reduce false positives and improve detection precision.
    • Ensure model outputs are interpretable and actionable for SOC analysts.

    Data Engineering for Security

    • Build and maintain data pipelines to collect, process, and transform security-relevant data (e.g., logs, network traffic, endpoint events) into ML-ready datasets.
    • Collaborate with security engineering team to ensure scalable and secure data handling (eg. parsing, processing, storage).

    AI Engineering & LLM-Powered Automation

    • Explore and build LLM-powered tools to automate repetitive SOC tasks (e.g., alert triage, evidence gathering, incident summarisation, report generation).
    • Apply appropriate guardrails and evaluation to ensure outputs are accurate, auditable, and safe to act on in operational contexts.

    Research & Innovation

    • Stay current on advancements in security data science, adversarial ML, and automated threat detection.
    • Prototype and test new ML and AI techniques (e.g., unsupervised anomaly detection, graph-based threat correlation).
    • Contribute to improving detection content through statistical analysis and clustering.

    Operations & Maintenance

    • Deploy models into production securely and responsibly, ensuring reliability and scalability.
    • Implement monitoring, alerting, and retraining mechanisms for deployed ML models.
    • Document methodologies and performance metrics for auditability and knowledge sharing.

What we are looking for:

  • Required

    • Proven experience in machine learning engineering or data science, ideally in a cybersecurity or operations context.
    • Proficiency in Python, with strong knowledge of ML frameworks.
    • Experience with data manipulation and analysis using Pandas, NumPy or similar tools.
    • Familiarity with security data sources (e.g., SIEM logs, EDR telemetry, network flow, authentication logs).
    • Solid understanding of ML lifecycle: data preparation, model training, evaluation, deployment, and monitoring.
    • Experience with data pipelines and storage technologies (e.g., Airflow, Kafka, Redis, Elasticsearch, Clickhouse, etc.).
    • Ability to work independently and collaborate effectively with both ML and security specialists.

    Preferred

    • Prior experience in threat detection, SOC operations, or security automation.
    • Knowledge of adversarial ML, graph analytics, or behavioral modeling in security contexts.
    • Experience integrating ML models into SIEM pipelines or automated detection frameworks.
    • Exposure to LLMs and AI engineering (e.g., prompt engineering, RAG, agent design), and awareness of LLM-specific risks like prompt injection and data leakage.

    Success in This Role

    • SOC analysts leverage ML-powered detections to identify threats faster.
    • Reduction in alert fatigue and false positives through adaptive and data-driven models.
    • Strong collaboration established between the security and MSA ML teams, sharing expertise and best practices.
    • Security data becomes more accessible, structured, and usable for analytical and predictive use cases.
    • New, intelligent detections, enrichment, and incident response automations become part of the SOC's standard toolkit.

Even if you don't meet all the requirements listed above, but feel you could still be a great fit, please still apply.

What We Offer:

  • Work that Matters: millions of people trust Proton with their privacy. We answer only to our users - not advertisers, not investors with conflicting agendas, not governments. The work you do here is real, and the impact is measurable. (read more about our impact here)
  • Technology: you'll get the right hardware and the right software you need to do your best work.
  • Learning & Development: we invest in your growth because sharp people make us better. Proton is one of the fastest ways to accelerate your career because you'll be thrown into real challenges, with real ownership, from day one.
  • Employee Benefits: your wellbeing isn't an afterthought. We offer strong health coverage, solid retirement options, generous leave, and wellness support so you can bring your best self to work every day
  • Stock Options: at Proton, we all have the opportunity to be owners of the company. From day one, you have a real stake in what we're building. When Proton wins, you win.
  • In-Person Collaboration: Amazing things happen when passionate, smart, and purposeful people get together in the same room. With offices across Geneva, Zurich, Barcelona, London and more, you'll spend most of your time collaborating face-to-face with people who genuinely care about what they're building
  • Food: Lunch and snacks are on us every day in our offices so you can focus on the work and not on what's for lunch.
  • Transport: getting to the office shouldn't cost you. We cover public transport, bike allowances, or parking, whichever works for you.
  • Flexible Working: you own your schedule. Set hours that work for you and your team - because outcomes matter more than when the clock says you started.

Our Commitment to Diversity and Inclusion

At Proton, we believe diversity drives innovation and strengthens our mission to provide privacy as a default for all. We are committed to fostering an inclusive environment where all individuals, regardless of race, ethnicity, gender, age, sexual orientation, physical ability, or socio-economic background, feel valued and empowered. We strive to create equal opportunities, promote open dialogue, and support continuous learning to ensure every voice is heard and respected.

If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know.

Candidate Privacy Notice

When you apply for a position, refer a candidate, or are considered for a role at Proton Technologies AG (Proton, we, us, or our), your information is stored in Greenhouse, in accordance with their Service Privacy Policy. This information is used to evaluate your suitability for the posted position. We also retain this information for consideration for future roles that you may apply for or that we believe may align with your background and skills.

If we no longer have a legitimate business need to process your information, we will either delete or anonymize it. Should you have any inquiries about how we use or manage your information, or if you wish to access, correct, or delete your data, please contact our privacy team at careers@proton.ch.

Proton does not accept unsolicited resumes from any sources other than directly from candidates. We will not pay a fee for any placement resulting from an unsolicited offer, even if the candidate is subsequently hired by Proton.

To learn more about our privacy policy, please visit our privacy policy page.

Compensation range
Paris:  46.000 - 74.000 gross annually*
Other locations: Compensation will be discussed during the interview process
*Final compensation will be determined based on the candidate's qualifications, skills, and previous experience

#LI-ONSITE