Ford

Machine Learning Engineer Interview Experience - Ciudad de Mexico, Mexico City

July 1, 2024

Positive ExperienceNo Offer

Process

It was a somewhat tiring interview, it lasted almost 2 hours.

It was completely in English with 2 engineers, both seemed to know very well what they were asking me about.

They asked me questions about:

ML fundamentals
MLOps, particularly MLFlow
Some basic systems engineering questions
Some algorithm scenarios to see if I had good practices.

Questions

Difference between regression and classification.

3 algorithms for each. How would you classify them?

As supervised or unsupervised learning?

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Interview Statistics

The following metrics were computed from 1 interview experience for the Ford Machine Learning Engineer role in Ciudad de Mexico, Mexico City.

Success Rate

0%

Pass Rate

Ford's interview process for their Machine Learning Engineer roles in Ciudad de Mexico, Mexico City is extremely selective, failing the vast majority of engineers.

Experience Rating

Positive100%

Neutral0%

Negative0%

Candidates reported having very good feelings for Ford's Machine Learning Engineer interview process in Ciudad de Mexico, Mexico City.

Ford Work Experiences

Low salary, but I love it

Machine Learning Engineer • Current Employee

Ciudad de Mexico, Mexico City, Mexico

Pros: - Work-life balance - Interesting and cutting-edge projects - Friendly culture - Interest in their employees - Amazing perks except for salary

Cons: - Growth inside is slow unless you negotiate with counter offers. - Getting an improvement in salary is slow.

Low salary, but I love it

Machine Learning Engineer • Current Employee

Ciudad de Mexico, Mexico City, Mexico

Pros: - Work-life balance - Interesting and cutting-edge projects - Friendly culture - Interest in their employees - Amazing perks except for salary

Cons: - Growth inside is slow unless you negotiate with counter offers. - Getting an improvement in salary is slow.

Good Learning, Limited Ml Scope

Machine Learning Engineer • Current Employee

Bengaluru, Karnataka, India

Pros: Best to upskill, learn. Good benefits.

Cons: In ML, no scope of developing newer technologies. Hike based on company performance.

Good Learning, Limited Ml Scope

Machine Learning Engineer • Current Employee

Bengaluru, Karnataka, India

Pros: Best to upskill, learn. Good benefits.

Cons: In ML, no scope of developing newer technologies. Hike based on company performance.

Poor mid management

Machine Learning Engineer • Current Employee

Dearborn, Michigan, United States

Pros: Good work-life balance, good benefits (insurance and holidays, including a two-week Christmas closure). Very good at bringing in new technologies.

Cons: Mid-managers are incompetent and micromanage. There's no real effort to retain talent.

Poor mid management

Machine Learning Engineer • Current Employee

Dearborn, Michigan, United States

Pros: Good work-life balance, good benefits (insurance and holidays, including a two-week Christmas closure). Very good at bringing in new technologies.

Cons: Mid-managers are incompetent and micromanage. There's no real effort to retain talent.

Low salary, but I love it

Machine Learning Engineer • Current Employee

Ciudad de Mexico, Mexico City, Mexico

Pros: - Work-life balance - Interesting and cutting-edge projects - Friendly culture - Interest in their employees - Amazing perks except for salary

Cons: - Growth inside is slow unless you negotiate with counter offers. - Getting an improvement in salary is slow.

4.0
Low salary, but I love it
Machine Learning Engineer • Current Employee
Ciudad de Mexico, Mexico City, Mexico
May 21, 2025
Pros: - Work-life balance - Interesting and cutting-edge projects - Friendly culture - Interest in their employees - Amazing perks except for salary
Cons: - Growth inside is slow unless you negotiate with counter offers. - Getting an improvement in salary is slow.

Good Learning, Limited Ml Scope

Machine Learning Engineer • Current Employee

Bengaluru, Karnataka, India

Pros: Best to upskill, learn. Good benefits.

Cons: In ML, no scope of developing newer technologies. Hike based on company performance.

4.0
Good Learning, Limited Ml Scope
Machine Learning Engineer • Current Employee
Bengaluru, Karnataka, India
June 23, 2025
Pros: Best to upskill, learn. Good benefits.
Cons: In ML, no scope of developing newer technologies. Hike based on company performance.

Poor mid management

Machine Learning Engineer • Current Employee

Dearborn, Michigan, United States

Pros: Good work-life balance, good benefits (insurance and holidays, including a two-week Christmas closure). Very good at bringing in new technologies.

Cons: Mid-managers are incompetent and micromanage. There's no real effort to retain talent.

2.0
Poor mid management
Machine Learning Engineer • Current Employee
Dearborn, Michigan, United States
March 23, 2025
Pros: Good work-life balance, good benefits (insurance and holidays, including a two-week Christmas closure). Very good at bringing in new technologies.
Cons: Mid-managers are incompetent and micromanage. There's no real effort to retain talent.

Ford Interview Questions

LRU Cache

Design a data structure that acts as a Least Recently Used (LRU) cache. Implement methods to get and put key-value pairs, evicting the least recently used entry when the cache is full.

Two Sum

Find two numbers in a given array that add up to a specific target value, and return their indices. Essentially, you need to efficiently locate the pair that satisfies the sum requirement.

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