Nike

Machine Learning Engineer Interview Experience

May 1, 2018

Neutral ExperienceNo Offer

Process

First, I talked to a recruiter in person.

After waiting approximately a week, I connected with a hiring manager.

The hiring manager went through my qualifications.

Different managers then look at your application to see the best fit.

Questions

Tell me about your background and qualifications.

Some very basic general programming questions, with Machine Learning concepts.

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Interview Statistics

The following metrics were computed from 4 interview experiences for the Nike Machine Learning Engineer role in United States.

Success Rate

0%

Pass Rate

Nike's interview process for their Machine Learning Engineer roles in the United States is extremely selective, failing the vast majority of engineers.

Experience Rating

Positive25%

Neutral50%

Negative25%

Candidates reported having mixed feelings for Nike's Machine Learning Engineer interview process in United States.

Nike Work Experiences

Chill job, no growth

Machine Learning Engineer • Current Employee

Pros: Easy job, lots of free time, and most talented engineers have unfortunately left.

Cons: No chance to get promoted, as this company does not believe in promotions, particularly in their technology department.

Chill job, no growth

Machine Learning Engineer • Current Employee

Pros: Easy job, lots of free time, and most talented engineers have unfortunately left.

Cons: No chance to get promoted, as this company does not believe in promotions, particularly in their technology department.

Like the company with no downsides

Machine Learning Engineer • Current Employee

Pros: I like the company very much.

Cons: No cons at all, like Nike.

Like the company with no downsides

Machine Learning Engineer • Current Employee

Pros: I like the company very much.

Cons: No cons at all, like Nike.

Good Work Culture

Lead Data Engineer • Current Employee

Pros: - No micromanagement - Trust in employees - Good work culture - Reputation means everything

Cons: - Some projects are too hectic. - Not much career growth options for experienced engineers.

Good Work Culture

Lead Data Engineer • Current Employee

Pros: - No micromanagement - Trust in employees - Good work culture - Reputation means everything

Cons: - Some projects are too hectic. - Not much career growth options for experienced engineers.

Chill job, no growth

Machine Learning Engineer • Current Employee

Pros: Easy job, lots of free time, and most talented engineers have unfortunately left.

Cons: No chance to get promoted, as this company does not believe in promotions, particularly in their technology department.

2.0
Chill job, no growth
Machine Learning Engineer • Current Employee
Portland, OR
May 6, 2026
Pros: Easy job, lots of free time, and most talented engineers have unfortunately left.
Cons: No chance to get promoted, as this company does not believe in promotions, particularly in their technology department.

Like the company with no downsides

Machine Learning Engineer • Current Employee

Pros: I like the company very much.

Cons: No cons at all, like Nike.

5.0
Like the company with no downsides
Machine Learning Engineer • Current Employee
Beaverton, OR
July 30, 2026
Pros: I like the company very much.
Cons: No cons at all, like Nike.

Good Work Culture

Lead Data Engineer • Current Employee

Pros: - No micromanagement - Trust in employees - Good work culture - Reputation means everything

Cons: - Some projects are too hectic. - Not much career growth options for experienced engineers.

4.0
Good Work Culture
Lead Data Engineer • Current Employee
Bengaluru
March 11, 2026
Pros: - No micromanagement - Trust in employees - Good work culture - Reputation means everything
Cons: - Some projects are too hectic. - Not much career growth options for experienced engineers.

Nike Interview Questions

Happy Number

Determine if a number is a 'happy number'. A happy number eventually reaches 1 when replaced by the sum of the squares of its digits, repeating the process until it does.

ArraysRecursionTwo Pointers

Can Place Flowers

You're given a flowerbed represented by an array of 0s and 1s, where 0 means empty and 1 means planted. Determine if you can plant a given number of new flowers without violating the rule that adjacent plots cannot be planted.

ArraysGreedy Algorithms

Diagonal Traverse

Traverse a matrix diagonally, returning the elements in a specific zig-zag order. You'll need to manage the direction and boundaries to output the elements correctly.

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