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Machine Learning Developer Intern Jobs in Waterloo, ON

Manulife

Data Scientist

Waterloo, ON · On-site

... machine learning use cases. * Productionize pipelines and datasets with monitoring, alerting, data quality checks, and performance tuning. * Collaborate with internal/external engineers and data ...

SAP

Senior Full Stack Engineer

Waterloo, ON · Hybrid

... Machine Learning/Artificial Intelligence and Industrial Internet of Things (IoT). The solution is ... Collaborate with DevOps resources and other technical experts to deliver on cloud projects like ...

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.

Syntronic

Senior Data Science Specialist

Waterloo, ON · On-site

CA$120K - CA$137K/yr

In this role, you will leverage advanced math, statistics, and machine learning to predict trends ... Data Engineering Optimization: Design efficient data loading, augmentation, and analysis techniques ...

BDO Canada

Senior Data Scientist, ASR

Kitchener, ON · On-site

CA$77K - CA$117K/yr

... machine learning models in a production environment. * Expertise in Python data science libraries like Pandas, matplotlib, NumPy, and Scikit-Learn. * Proficiency in programming languages such as ...

Jetson Home

Data & ML Engineer

Kitchener, ON

You'll gain experience applying data and machine learning to real-world control problems--where ... That context will make you a stronger engineer and a better decision-maker. * Shape our data and ML ...

Actalent

Senior Data Engineer/Analyst

Waterloo, ON

Data Science and Machine Learning Specialist Join a Connected Vehicle Analytics Data Team that ... Partner closely with vehicle embedded engineers, product owners, and technical product managers to ...

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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

Data Scientist

Manulife

Waterloo, ON • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

We'rebuilding AI products that move from promising prototypes to reliable, production-grade systems with measurable business impact. This role blendsLLM application engineering, applied data science, anddata engineering fundamentals.

You will own the end-to-end data operations lifecycle: sourcing and understanding data, designing scalable pipelines, enabling analytics and model development, and partnering with engineering and data science to productionize solutions. You will translate complex data into context for humans and AI applications, implement durable processes.

You'lldesign, evaluate, deploy, and continuously improve GenAI systems (RAG, agentic workflows, model fine-tuning) while helping shape the data foundation that makes them trustworthy at scale.

Position Responsibilities:

  • Design, evaluate, and deployRAG pipelines, agentic systems, and chat interfaces, including advanced retrieval methods and modular designs.
  • ConductLLM red-teaming, bias detection, and alignment testing; buildautomated evaluation frameworksand develop measurement/feedback loops.
  • GenAI engineering in the Azure ecosystem:integrate and test LLMs usingOpenAI APIs,Azure AI Services,Azure AI Search/Cognitive Search,Azure ML,Databricks, and (where applicable)AKS/Kubernetes.
  • Develop and implement ML models (traditional + GenAI) anddesign/execute experimentstovalidate,optimize, and scale solutions.
  • Contribute tofine-tuning and pre-training pipelinesfor domain use cases; usesynthetic data generationand creative data sourcing to improve modeling outcomes (including sparse/rare-event problems).

Data acquisition & domain understanding

  • Identify, evaluate, and obtain access to internal and external data sources with minimal guidance.
  • Partner with subject matter experts to understand data definitions, quality, lineage, and business context.
  • Document datasets using standard templates (metadata, assumptions, refresh cadence, known issues) and present findings to stakeholders.

Data engineering & platform delivery

  • Design, build, andmaintainrobust ETL/ELT pipelines to extract, transform, and stage data for AI/ML and BI consumption.
  • Create and manage tables, schemas, and databases; implement data models that support analytics and machine learning use cases.
  • Productionize pipelines and datasets with monitoring, alerting, data quality checks, and performance tuning.
  • Collaborate with internal/external engineers and data scientists to integrate data science solutions into production systems.

Analytics, measurement & reporting

  • Deliver ad-hoc analysis, business analytics, and reporting for projects of moderate scope/complexity.
  • Define metrics andacquiredata to measure solution effectiveness; communicate results and recommendations to peers and stakeholders.
  • Build dashboards and reporting assets (e.g., Tableau/Power BI/Qlik) to support decision-making.

Process design & operational excellence

  • Help design scalable operating processes to implement analytics/AI insights, including:
  • Clear roles and responsibilities across partners
  • Defined workflows, system/data flows, and contingencies
  • Checks-and-balances (validation, QA, approvals)
  • KPI tracking andclosed-looplearning to continuously improve outcomes

Communication & mentorship

  • Partner with Data Engineers, ML Engineers, BI, IT, and business leaders;participatein code/model reviews, documentation, agile delivery, and mentorship.
  • Communicate moderately complex technical and analytical topics to senior team members and business partners.
  • Build a strong internal network andleveragesenior peers to accelerate delivery.

Required Qualifications:

Education & experience

  • Bachelor's degree in Computer Science, Engineering, Math, or equivalent practical experience.
  • 2+ years of relevant experience in data engineering, analytics engineering, or BI/analytics roles supporting AI/ML or advanced analytics.
  • Advanced degree (MS/PhD) in a quantitative field or equivalent depth through impactful work; publications or research contributions are a plus.

Technical skills

  • Strong programming skills in Python; advanced SQLproficiency; Java experience is asset.
  • Advanced experience with data transformation and modeling for analytics/BI and ML feature readiness.
  • Strong understanding of relational databases and data modeling concepts.
  • Working knowledge of distributed computing concepts/tools.
  • Advanced experience with data visualization tools

Analytics/ML foundations

  • Ability to explore and mine large structured and unstructured datasets using a systematic approach.
  • Familiarity with statistics and common analytical techniques (e.g., regression, clustering, PCA, decision trees, survival analysis).
  • Basic understanding of machine learning algorithms and familiarity with common AI/ML toolkits.
  • Hands-on experience with RAG, embeddings, semantic search, and vector databases (e.g., FAISS, MongoDB, Neo4j) and/or graph-based analytics.
  • Knowledge of GenAI frameworks such as LangChain, Semantic Kernel, and agent frameworks (e.g.,Autogen/LangGraph/CrewAI-style tools).

(Optional) Include with your application

  • 1-2 examples of work (GitHub, write-ups, papers, demos, etc.) showing:
  • something you built end-to-end,
  • how you evaluated quality and failure modes,
  • and how you iterated based on evidence and constraints.

When you join our team:

  • We'llempower you to learn and grow the career you want.
  • We'llrecognize and support you in a flexible environment where well-being and inclusion are more than just words.
  • As part of our global team,we'llsupport you in shaping the future you want to see.

#LI-Hybrid

The role being advertised is an existing vacancy.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.

Referenced Salary Location

Toronto, Ontario

Working Arrangement

Hybrid

Salary range is expected to be between

$94,430.00 CAD - $144,430.00 CAD

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact hr@manulife.com for the salary range for your location.

Manulife offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence. If you are applying for this role in the U.S., please contact hr@manulife.com for more information about U.S.-specific paid time off provisions.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.

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