Machine Learning Engineer Interview Experience - Toronto, Canada
January 27, 2026
Positive ExperienceGot Offer
Process
I applied through an employee referral.
First round was screening with one of the hiring managers. Second round was a 3-hour technical interview (coding + going through your past experience/project). Last round was a behavioral interview with HR.
Questions
Finding all the bugs from a piece of code
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Interview Statistics
The following metrics were computed from 9 interview experiences for the Qualcomm Machine Learning Engineer role in Toronto, Ontario.
Success Rate
44%
Pass Rate
Qualcomm's interview process for their Machine Learning Engineer roles in Toronto, Ontario is fairly selective, failing a large portion of engineers who go through it.
Experience Rating
Positive56%
Neutral44%
Negative0%
Candidates reported having very good feelings for Qualcomm's Machine Learning Engineer interview process in Toronto, Ontario.
Qualcomm Work Experiences
3.0
Great benefits, weak and complacent management
Machine Learning Engineer • Current Employee
San Diego, California, United States
April 15, 2018
Pros: Good work/life balance, flexible hours
Cons: Apathetic management.
Disconnect between product and engineering teams.
Company increasingly lacks strategic direction.
Promotions often based on politics rather than ability.
4.0
Great work-life balance
Machine Learning Engineer • Current Employee
Bengaluru, Karnataka, India
July 8, 2022
Pros: Freedom to research on your topics of interest.
Full ownership of your work. The managers will only comment or suggest modifications. You'll feel as if this is YOUR project you're working on.
Cons: Somewhat lagging in terms of compensation.
2.0
Great Pay, Useless Work
Machine Learning Engineer • Current Employee
San Diego, California, United States
February 15, 2024
Pros: Good pay for ML engineers.
Cons: - Work begins with no clear requirement or planning.
- Because of point 2, it's usually found out later that we were working on something useless.
- A lot of demo tasks get disposed of afterward; codebases are messy.
- 3.0Great benefits, weak and complacent managementMachine Learning Engineer • Current EmployeeSan Diego, California, United StatesApril 15, 2018Pros: Good work/life balance, flexible hoursCons: Apathetic management. Disconnect between product and engineering teams. Company increasingly lacks strategic direction. Promotions often based on politics rather than ability.
- 4.0Great work-life balanceMachine Learning Engineer • Current EmployeeBengaluru, Karnataka, IndiaJuly 8, 2022Pros: Freedom to research on your topics of interest. Full ownership of your work. The managers will only comment or suggest modifications. You'll feel as if this is YOUR project you're working on.Cons: Somewhat lagging in terms of compensation.
- 2.0Great Pay, Useless WorkMachine Learning Engineer • Current EmployeeSan Diego, California, United StatesFebruary 15, 2024Pros: Good pay for ML engineers.Cons: - Work begins with no clear requirement or planning. - Because of point 2, it's usually found out later that we were working on something useless. - A lot of demo tasks get disposed of afterward; codebases are messy.
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