Time since we first saw it
Day 22
Similar jobs usually come down between day 8 and day 76.
At Cibc, jobs usually come down by about day 12.
From 5,496 similar postings that came down, and 148 of Cibc’s. Coming down is not always a hire.
Machine Learning Engineer Co-op
Toronto, ON
Live, first seen by us 22 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Temporary · Full-time — employment source
Employment Type Temporary (Fixed Term) Weekly Hours
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- New graduates
- For current students
Job title: Machine Learning Engineer Co-op
- Work authorization
- Must already have the right to work
You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit
What you’ll bring
All qualificationsCore experience
- Familiarity in using Git, GitHub or other version control tools is an asset.
Qualification wording
You have strong Tech Skills: You demonstrate good programming skills and have knowledge of data science & machine learning with Python using common data science libraries, such as the PyData stack, and other ML frameworks. You have Azure and cloud related knowledge. It is also an asset if you have a knowledge of writing efficient modular codes in an non-notebook environment along hands-on experience building end-to-end solutions with Large Language Models. Familiarity in using Git, GitHub or other version control tools is an asset.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 22, 202622 days ago
- Recorded sightings
- 38
- Last seen by us
- Nov 14, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Cibc is hiring
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down quickly
- 9% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Azure
Where the posting names them
- Data Science Expertise: You will use your knowledge in Machine Learning to contribute towards the development of reproducible models. - MLOps: You will utilize your Python programming skills to refactor experimental notebooks into production grade Python modules using functional programming. You will assist with tasks related to the deployment of machine learning models and the maintenance of internal Python libraries - Champion Best Practices: You will adhere to the team’s code-style, work-flow patterns and project structure standards. You will participate in writing great documentation, practicing test-driven-development and properly annotating your code.
Who you are - You have strong Tech Skills: You demonstrate good programming skills and have knowledge of data science & machine learning with Python using common data science libraries, such as the PyData stack, and other ML frameworks. You have Azure and cloud related knowledge. It is also an asset if you have a knowledge of writing efficient modular codes in an non-notebook environment along hands-on experience building end-to-end solutions with Large Language Models. Familiarity in using Git, GitHub or other version control tools is an asset. - You're driven by collective success. You know that collaboration can transform a good idea into a great one. You understand the power of an inclusive team that enjoys working together to bring a shared vision to life.
Skills DevOps, Generative AI, GitHub Actions, Machine Learning (ML), Python (Programming Language), Software Development
Your next step
Complete your application on cibc.wd3.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
- You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
- “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
We’re building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what’s right for our clients.
At CIBC, we embrace your strengths and your ambitions, so you are empowered at work. Our team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute.
To learn more about CIBC, please visit CIBC.com
What you'll be doing
CIBC’s Enterprise AI Infrastructure & ML Ops team is hiring a Machine Learning Engineer Co-op. As an ML Engineer Co-op, you will collaborate on the MLOps strategy, assist with adherence to enterprise governance, and support in the implementation of tooling and frameworks to enable secure, scalable, and repeatable AI/ML delivery across the bank. Success will be built on supporting technical activities to standardize capabilities and create a measurable impact in building influence with stakeholders.
At CIBC we enable the work environment most optimal for you to thrive in your role. Details on your work arrangement (proportion of on-site and remote work) will be discussed at the time of your interview)
Important
- We may ask you to complete an attribute-based assessment and other skills tests (such as simulation, coding, French proficiency, MS Office). Our goal for the application process is to get to know more about you, all that you have to offer, and give you the opportunity to learn more about us.
- You must be currently enrolled in post-secondary education and returning to full-time studies to be eligible. However, you do not need to be in a registered Co-Op program to be considered for a role.
- Recruitment timeline: Applications review – Oct/ Nov; Interviews – Nov; Offers - Nov
- Please include your resume (no more than 2 pages), a cover letter (no more than 1 page), and your most recent unofficial transcript with your application. These should all be uploaded into the Resume section of the application as one pdf document
- This is an 8 month co-op opportunity.
How you'll succeed
- Data Science Expertise: You will use your knowledge in Machine Learning to contribute towards the development of reproducible models.
- MLOps: You will utilize your Python programming skills to refactor experimental notebooks into production grade Python modules using functional programming. You will assist with tasks related to the deployment of machine learning models and the maintenance of internal Python libraries
- Champion Best Practices: You will adhere to the team’s code-style, work-flow patterns and project structure standards. You will participate in writing great documentation, practicing test-driven-development and properly annotating your code.
Who you are
- You have strong Tech Skills: You demonstrate good programming skills and have knowledge of data science & machine learning with Python using common data science libraries, such as the PyData stack, and other ML frameworks. You have Azure and cloud related knowledge. It is also an asset if you have a knowledge of writing efficient modular codes in an non-notebook environment along hands-on experience building end-to-end solutions with Large Language Models. Familiarity in using Git, GitHub or other version control tools is an asset.
- You're driven by collective success. You know that collaboration can transform a good idea into a great one. You understand the power of an inclusive team that enjoys working together to bring a shared vision to life.
- You have a strong sense of intellectual curiosity. You are intellectually curious and often think about ways to improve how we work. You may not know every tool or framework, but your innate sense of curiosity drives you to learn and grow your technical and business acumen.
- Values matter to you. You bring your real self to work and you live our values – trust, teamwork and accountability.
What CIBC Offers
At CIBC, your goals are a priority. We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential.
We work to recognize you in meaningful, personalized ways including a competitive compensation, a banking benefit*, wellbeing support and additional offers such as employee and family assistance programs and MomentMakers, our social, points-based recognition program.
Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.
*Subject to program terms and conditions
What you need to know
CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation, please contact Mailbox.careers-carrieres@cibc.com
CIBC is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise.
You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit
We may ask you to complete an attribute-based assessment and other skills test (such as simulation, coding, French proficiency).
We use artificial intelligence tools during the recruitment process. Our goal for the application process is to get to know more about you, all that you have to offer, and give you the opportunity to learn more about us.
Expected End Date
2027-08-20Job Location
Toronto-81 Bay, 16th FloorEmployment Type
Temporary (Fixed Term)Weekly Hours
37.5Skills
DevOps, Generative AI, GitHub Actions, Machine Learning (ML), Python (Programming Language), Software DevelopmentSource details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Toronto, ON
CIBC’s Enterprise AI Infrastructure & ML Ops team is hiring a Machine Learning Engineer Co-op. As an ML Engineer Co-op, you will collaborate on the MLOps strategy, assist with adherence to enterprise governance, and support in the implementation of tooling and frameworks to enable secure, scalable, and repeatable AI/ML delivery across the bank. Success will be built on supporting technical activities to standardize capabilities and create a measurable impact in building influence with stakeholders. At CIBC we enable the work environment most optimal for you to thrive in your role. Details on your work arrangement (proportion of on-site and remote work) will be discussed at the time of your interview) Important
- Work authorization
- CIBC is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise. - You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit - We may ask you to complete an attribute-based assessment and other skills test (such as simulation, coding, French proficiency).