1

Internship Machine Learning Engineer Jobs in Hamilton, ON

Utilize machine learning techniques to improve customer segmentation, churn prediction, and ... Engineer features by using your business acumen to find new ways to combine disparate internal and ...

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 ...

Our Software Engineering team is currently developing end-to-end real-time solutions for the public ... Machine Learning (ML), Big Data Analytics, and Decision Support Systems (DSS). Larus has three core ...

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

... and Engineering, focusing on innovations in Artificial Intelligence, Machine Learning, and Data Science.​ We invite enthusiastic and qualified applicants to submit their cover letter and resume ...

Showing results 41-60

Internship Machine Learning Engineer information

What does an internship machine learning engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

What types of projects and responsibilities can I expect as an internship machine learning engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What are the key skills and qualifications needed to thrive as an internship machine learning engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.

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

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What are the most commonly searched types of Machine Learning Engineer jobs in Hamilton, ON?

The most popular types of Machine Learning Engineer jobs in Hamilton, ON are:

What cities near Hamilton, ON are hiring for Internship Machine Learning Engineer jobs?

Cities near Hamilton, ON with the most Internship Machine Learning Engineer job openings:

Senior Automation Developer - Assistant Vice President

Citi

Mississauga, ON • On-site

Full-time

Posted 24 days ago


Citibank rating

8.4

Company rating: 8.4 out of 10

Based on 179 frontline employees who took The Breakroom Quiz

39th of 174 rated banks


Job description

We are seeking a highly skilled Senior Automation Developer for a fully hands-on, programmatic engineering role dedicated to architecting, refactoring, and maintaining scalable, distributed test automation frameworks for complex, multi-tier User Interfaces (UI) and decoupled server-side microservices. This engineering-centric position requires treating test suites as first-class software products, applying rigorous object-oriented design patterns (such as Page Object Model, Singleton, and Factory patterns) and SOLID design principles to eliminate manual verification bottlenecks and minimize technical debt. Operating within a high-velocity Agile Scrum environment, you will collaborate closely as full-stack automation application developers and with product owners to implement shift-left testing methodologies, designing testability directly into the system architecture from the earliest stages of the software development lifecycle (SDLC).

A core focus of this role is the integration of advanced Artificial Intelligence (AI) and Machine Learning (ML) utilities to enable self-healing element locators, accelerate programmatic script generation, and perform predictive analytics on test execution telemetry. Ultimately, you will bridge the gap between development and operations by engineering highly parallelized, deterministic automation pipelines that facilitate continuous integration and continuous deployment (CI/CD) with zero-downtime delivery. Responsibilities: Framework Architecture & Design: Architect, implement, and scale robust, object-oriented automation frameworks for UI and Server-side components, prioritizing highly reusable Selenium-based architectures (e.g., Page Object Model, Page Factory, and BDD-Cucumber)

Hands-On Programmatic Engineering: Write clean, maintainable, and production-grade code to develop complex test automation artifacts, including custom libraries, utility functions, and dynamic test scenarios. Shift-Left Collaboration: Collaborate with cross-functional engineering teams during early-stage sprint planning and grooming to identify automation requirements, define technical acceptance criteria, and establish robust testability hooks within the application code. Methodology Implementation: Implement and advocate for Behavior Driven Development (BDD) and Test Driven Development (TDD) methodologies, translating Gherkin feature files into executable step definitions.

Server-Side Validation: Develop and execute automated validation suites for server-side components, including RESTful APIs, microservices, and database layers using SQL and NoSQL queries. AI Tool Integration: Explore, evaluate, and integrate cutting-edge AI tools and machine learning utilities to enable self-healing test scripts, automate visual regression, and optimize test coverage. Defect & Execution Analysis: Analyze automated execution failures, debug complex script or environment issues, and work closely with development teams to resolve defects rapidly.

Recommended Qualifications: 5-8 years of relevant experience in software development. Programming Languages: Advanced, hands-on programming proficiency in core languages including Java, Python, and JavaScript/TypeScript, with a deep understanding of object-oriented programming (OOP) principles, data structures, and algorithms. Development Tools & IDEs: Extensive experience utilizing modern Integrated Development Environments (IDEs), specifically IntelliJ IDEA, for writing, debugging, and refactoring clean, high-quality automation code.

AI-Assisted Development: Hands-on experience leveraging AI coding assistants, specifically GitHub Copilot, to accelerate script generation, refactor legacy code, and optimize test automation workflows. Professional Experience: Proven professional experience in a hands-on software development or automation engineering role, with deep expertise in Selenium WebDriver and associated frameworks. CI/CD Pipeline Integration: Hands-on experience configuring, maintaining, and optimizing continuous integration and continuous delivery (CI/CD) pipelines (e.g., Jenkins, GitLab CI, GitHub Actions, Tekton) to trigger automated test suites

Containerization & Orchestration: Experience orchestrating automated regression runs within containerized environments using Docker and Kubernetes via pipeline-as-code configurations. Version Control: Strong familiarity with version control systems (Git), branching strategies, and pull request workflows within an enterprise environment. Core Competencies: Excellent analytical, problem-solving, and technical communication skills, with the ability to articulate complex architectural concepts to diverse stakeholders.

Education: Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical hands-on software development experience. This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location Full Time Salary Range: $94,300.00 - $141,500.00 ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening

Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi. Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making.

Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details. ------------------------------------------------------ This job opening is for an existing job vacancy. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.


What Citibank employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Citigroup Inc logo

About Citigroup Inc

Sourced by ZipRecruiter

We live in an increasingly complex world. Companies these days are either born global or are going global at record speed. Business and geopolitics are forging an entirely new dynamic and consumers now expect financial services to be a seamless part of their digital lives. Citi is a bank that’s uniquely positioned for this moment. Through our vast global network and our on-the-ground expertise, we can connect the dots, anticipate change and empathize the needs of our clients and customers in ways that other banks simply cannot. Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We have set expectations for how we must act to bring our mission to life. These expectations are at the heart of our Leadership Principles – we take ownership, we deliver with pride and we succeed together.

Industry

Banking and credit intermediation

Company size

5,001 - 10,000 Employees

Headquarters location

New York City, NY, US