Machine Learning Engineer Interview Experience - Toronto, Ontario
Process
I initially completed an online assessment that took at least an hour and a half.
Afterward, I received an email from HR and had a 30-minute conversation about the company, the role, and the next steps.
Following that, I had a one-hour interview where we discussed the position in more detail, and I had the opportunity to share my experience and skills.
While I felt the interview went okay, I expected at least an update on the status of my application. After waiting a week with no response, I reached out to them for an update and was told they'd discuss it with the interviewer and get back to me as soon as possible.
It's now been a month, and I'm disappointed that I haven't even received a generic update, especially after investing three hours in interviews, not to mention the time spent on preparation. What a waste of time!
Questions
What are the challenges in solving the speech-to-text problem?
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Interview Statistics
The following metrics were computed from 2 interview experiences for the SoundHound Machine Learning Engineer role in Toronto, Ontario.
Success Rate
SoundHound's interview process for their Machine Learning Engineer roles in Toronto, Ontario is extremely selective, failing the vast majority of engineers.
Experience Rating
Candidates reported having very negative feelings for SoundHound's Machine Learning Engineer interview process in Toronto, Ontario.
SoundHound Work Experiences
- 1.0Dumpster fireMachine Learning Engineer • Former EmployeeApril 18, 2023Pros: Highly competent colleagues Super nice colleagues Highly technical companyCons: Low morale due to 50% of staff being laid off Complete disorganization Even if the company is very engineering oriented, some engineering roadblocks have not been solved for years
- 3.0mixedMachine Learning Engineer • Former EmployeeSanta Clara, CAMarch 14, 2023Pros: Remote friendly. Good office lunch.Cons: Teams spread over the world. Had laid off about half of the staff early this year due to financial issues.
- 3.0Once Great Environment but ...Machine Learning Engineer • Current EmployeeFebruary 5, 2023Pros: Once a great place, where you can find interesting and challenging projects, talented peers, loose environment of innovation with fault tolerance.Cons: However, everything changed since the slowing down of business after spac. The environment is becoming pushing, short-sighted, and chaotic. Company didn't show any respect and caring for the talents, a lot of those who has been supporting the company for no less than 3 years. No CXO level claimed to be responsible for the layoffs, or business failure, while only the employee became the sacrifice of those wrong business directions, irrational expansion.
SoundHound Interview Questions
