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Engineering Knowledge Management Intern; Fall

Job in Toronto, Ontario, C6A, Canada
Listing for: Hitachi Rail
Full Time, Contract, Apprenticeship/Internship position
Listed on 2026-05-27
Job specializations:
  • Engineering
Salary/Wage Range or Industry Benchmark: 23 - 30 CAD Hourly CAD 23.00 30.00 HOUR
Job Description & How to Apply Below
Position: Engineering Knowledge Management Intern (Fall 2026, 8 months)
About UsA career at Hitachi Rail will help create a legacy. With operations in every corner of the world, our work goes to the cutting-edge of digital transformation and technology. From the multi-cultural strength of our global organisation to the sustainable and innovative ways we work to bring people together, there’s something for everyone to get stuck into. And that’s where you come in.

Toronto, Ontario, Canada (Hybrid)

Job Title:

:
Engineering Knowledge Management Intern Rail Pass Type:
Internship/Co-op (Full-time/Hybrid)
Departure and Arrival Date (Start
-End):
September 2026 - August 2027 (12months)
Vacancy: 1

Location:

100 Consilium Place, Scarborough, ON M1H 3E3

Work hours/week: 40

Pay Details: $23-$30 CAD hourly

Stations on Your Journey:

Welcome and Onboarding Station Intern Orientation Online Onboarding Curriculum Buddy Program for mentorship and guidance

Hands-On Work Station Real-world projects with top industry talent

Paid internship + paid vacation

Hybrid work model

A chance to build your career with a global leader driving digital transformation and innovation that helps support sustainable future

Networking Station"Ask Me Anything" with the Executive Committee Employee Resource Groups (ERGs)
Social Intern Events:
Coffee Breaks, Onsite/Offsite events

Business Intern Events:
Intern Showcase & Graduation ceremony

Company Social Events:
Holiday Party, Employee BBQs, Golf tournament, etc.

This role is about creating clarity from complexity. Our training materials are currently spread across multiple formats maintained by different international teams. Your job is to consolidate, structure, and maintain this into a coherent system that engineers can use efficiently. You will also document decisions made during key engineering meetings, ensuring knowledge is captured and accessible.

You will work closely with discipline referents across systems, software, ITV, safety, and configuration management to extract and structure their knowledge into reusable training materials. This is a local team role with visibility into how a global engineering platform operates.

This internship gives you hands-on experience in high-level engineering discussions, allowing you to learn about how the whole V-Cycle is handled in a large-scale organization:

ALM Platform Management:
How large organizations manage requirements, tests, and traceability across the full product lifecycle

Requirements Engineering:
The structure behind how safety-critical rail systems are specified, reviewed, and approved

Technical Writing at Scale:
Creating materials that engineers across disciplines can use efficiently

Process Governance:
How engineering change control processes work in regulated industries

This placement is defined to make your profile AI-proof by allowing you to demonstrate your ability to handle real-world complex multi-disciplinary tasks.

Key Responsibilities Collaborating with colleagues across all engineering disciplines to define and document process into a unified project hosted within our ALM tool.

Contribute creative ideas and prototypes to structure learning paths for users at varying expertise levels (new user, intermediate, advanced)
Create how-to guides, cheat sheets, and reference pages for common platform tasks

Help Process Referents in the creation of Training modules (and maintain a training content inventory: what exists, what needs updating, what is missing)
Present their findings and recommendations to peers and senior stakeholders

When required, develop prototypes of Polarion Reports based on defined requirements

Required Skills and Experience Experienced in preparing and giving presentations

Experienced in exploring and evaluating data Experienced in writing documentation, training materials, or tutorials

Experienced in using AI tools and leveraging their capabilities

Demonstrates curiosity, willingness to learn, autonomy, and poised to find an effective solutions

Able to work full time (40 hours) for the agreed work term with a minimum of 2 days (16 hours) in the Toronto office

Fluent in English both in written and oral communication

Strong in organizational skills and their ability to balance multiple priorities

The…
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