AI & ML Intern - Electrical Engineer (Winter 2027)

Trench Group; Toronto; On-site; CAD 68,770,000 - 85,962,000; Full time

Benefits offered by this job

Hourly rate $24–$30

Job summary

Trench Canada in Scarborough, ON is offering a full-time internship (8-12 months) for students. You will assist in designing, developing, and testing internal web applications to support air core reactor design and production.

Collaborate with the R&D team to identify automations and AI-driven solutions, develop AI/ML models using Python, and ensure outputs are physically meaningful within engineering standards. On-site work required.

Qualifications

• Bachelor's degree in Electrical Engineering or related field.
• Foundational knowledge of power systems, electromagnetics, circuit design, and control.
• Exposure to relational databases and SQL.
• Strong English communication skills.
• On-site work in a team-oriented R&D environment.
• Proficiency with Python and ML libraries (TensorFlow or PyTorch).
• Exposure to generative AI/ML concepts in engineering contexts.
• Familiarity with web app frameworks (Angular, React, Vue or Flask).
• Understanding of transformer or reactor design principles.
• Ability to read electrical engineering documentation.
• Github profiles submission required.

Responsibilities

• Assist in the design, development, and testing of internal web applications to support the design and production of air core reactors.
• Collaborate with the R&D team to identify automations and AI-driven solutions for engineering workflows.
• Develop and integrate AI and ML models using Python and libraries into practical tools.
• Apply power systems knowledge to validate AI/ML outputs and ensure engineering compliance.
• Support user-friendly interfaces for engineering staff to interact with AI features.
• Participate in requirement gathering with engineers to ensure tools meet real needs.
• Document development processes, tool functionalities, and technical decisions.
• Contribute to testing and iterative improvement of tools based on feedback.
• Stay current with emerging AI/ML techniques for Trench Coils engineering challenges.

Skills

English proficiency

Team collaboration

Research & development

Education

Bachelor's degree in Electrical Engineering

Tools

Python

TensorFlow

PyTorch

SQL

Web Frameworks

Job description

Scarborough, ON | Full-Time Internship (8-12 months) |Student (not graduated yet)

About Us

In Trench Canada, we deliver state-of-the-art, safe, and reliable instrument transformers, coils, and bushings for seamless energy transmission. With a legacy of customized engineering and innovation, we enable society to harness the power of electricity with reliability and performance.

We are driven by a commitment to advancing the energy sector through innovative technology and sustainable practices. Our culture emphasizes continuous improvement, attention to detail, and adaptability, while fostering an inclusive and respectful environment where diverse perspectives are valued and everyone has the opportunity to contribute and succeed.

Our Values

• Trust
• Responsibility
• Excellence
• Navigating Change
• Candor
• Humility

Overview

Your Tasks

• Assist in the design, development, and testing of internal web applications to support the design and production of air core reactors.
• Collaborate with the R&D team to identify manual or repetitive engineering workflows that can be improved through software and AI-driven solutions.
• Develop and integrate AI and Machine Learning models using Python and relevant libraries (such as TensorFlow or PyTorch) into practical engineering tools.
• Apply knowledge of power systems, electromagnetic theory, and circuit design to validate and verify AI/ML model outputs, ensuring results are physically meaningful and aligned with engineering standards.
• Support the implementation of user-friendly interfaces that allow engineering staff to interact with AI-powered features seamlessly.
• Participate in requirement gathering sessions with engineers to ensure developed tools meet real operational needs.
• Document development processes, tool functionalities, and technical decisions clearly and consistently.
• Contribute to testing and iterative improvement of tools based on team feedback.
• Stay current with emerging AI/ML techniques and propose approaches applicable to Trench Coils' engineering challenges.

Requirements

• Bachelor's degree in Electrical Engineering or a related field.
• Foundational knowledge of power systems, electromagnetic theory, circuit design, and control systems.
• Exposure to relational databases and SQL.
• Strong written and verbal communication skills in English.
• Ability to work on-site in a collaborative, team-oriented R&D environment.
• Proficiency with Python and ML libraries (such as TensorFlow or PyTorch).
• Exposure to generative AI/ML concepts applied to engineering or industrial contexts.
• Familiarity with web application frameworks (e.g., Angular, React, Vue or Flask).
• Understanding of transformer or reactor design principles.
• Ability to read and interpret electrical engineering documentation and specifications.
• Applicants must submit their Github profiles alongside resumes.

We Offer

• You will work in a motivated team on forward-looking projects and gain insights into the latest technologies.
• Support from experienced professionals in handling the latest measurement technology.
• An hourly rate of pay of $24 - $30.

Our Commitment to Inclusion and Accessibility

Trench is an equal opportunity employer and is committed to building a diverse and inclusive workforce. We welcome applications from all qualified individuals and provide accommodations for applicants with disabilities throughout the recruitment and selection process. If you require accommodation or support at any stage of the application or interview process, please contact us and we will work with you to meet your needs.

Use of Artificial Intelligence in Recruitment

Trench uses artificial intelligence and automated tools as part of its recruitment and screening processes to support efficient and fair candidate evaluation.