Machine Learning Engineer Interview Experience - United States
November 8, 2019
Positive ExperienceNo Offer
Process
First, you will be asked about past experiences and projects. This may include topics such as:
- The challenges you encountered.
- Why you chose a specific model.
- The pros and cons of your model.
- The outcome of your projects.
Following this, a case question will be given, and you will be asked to write code using machine learning methods to solve it.
Questions
Given a certain form of data, the task is to write code to predict the classes.
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Interview Statistics
The following metrics were computed from 8 interview experiences for the Zillow Machine Learning Engineer role in United States.
Success Rate
0%
Pass Rate
Zillow's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Positive38%
Neutral0%
Negative63%
Candidates reported having very negative feelings for Zillow's Machine Learning Engineer interview process in United States.
Zillow Work Experiences
3.0
Used to be great; ZO winddown was a huge blow
Machine Learning Engineer • Former Employee
Seattle, WA
March 29, 2023
Pros: Work Life Balance Benefits Remote-first
Cons: Stock decline Lack of innovation
5.0
Overall great company to work for
Machine Learning Engineer • Former Employee
Seattle, WA
January 4, 2022
Pros: Great work/life balance and culture
Reasonably good tech stack in some parts of the company
Cons: Some parts of the company run on very outdated technology
Product/engineering is largely driven by real-estate business, so feels less techy than other companies like Microsoft, Amazon, or Google.
Need to do a fair amount of prancing to get visibility for promotion, but I guess it's inevitable at that size.
4.0
Great but not the best
Machine Learning Engineer • Current Employee
October 9, 2021
Pros: - Scale of impact
- Technology stack
- Coworkers
- Remote work
Cons: - Politics in terms of promotions, projects, headcount, etc
- Fail first mentality in multiple production services, leading to annoying oncall
- WLB is org-dependant
- 3.0Used to be great; ZO winddown was a huge blowMachine Learning Engineer • Former EmployeeSeattle, WAMarch 29, 2023Pros: Work Life Balance Benefits Remote-firstCons: Stock decline Lack of innovation
- 5.0Overall great company to work forMachine Learning Engineer • Former EmployeeSeattle, WAJanuary 4, 2022Pros: Great work/life balance and culture Reasonably good tech stack in some parts of the companyCons: Some parts of the company run on very outdated technology Product/engineering is largely driven by real-estate business, so feels less techy than other companies like Microsoft, Amazon, or Google. Need to do a fair amount of prancing to get visibility for promotion, but I guess it's inevitable at that size.
- 4.0Great but not the bestMachine Learning Engineer • Current EmployeeOctober 9, 2021Pros: - Scale of impact - Technology stack - Coworkers - Remote workCons: - Politics in terms of promotions, projects, headcount, etc - Fail first mentality in multiple production services, leading to annoying oncall - WLB is org-dependant
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