Meta

Software Engineer - Machine Learning Interview Experience - California City, California

November 1, 2025

Positive ExperienceNo Offer

Process

Tech screen of 45 minutes with one medium and one easy LeetCode-style question.

Range sum for BST.
Balance parenthesis.

I completed the second one properly. For the first one, I wrote the whole code and explained everything. I just had to correct one line, but I answered all questions correctly. Despite this, I was still rejected.

Questions

Range sum for BST
Balance parenthesis.

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Interview Statistics

The following metrics were computed from 1 interview experience for the Meta Software Engineer - Machine Learning role in California City, California.

Success Rate

0%

Pass Rate

Meta's interview process for their Software Engineer - Machine Learning roles in California City, California is extremely selective, failing the vast majority of engineers.

Experience Rating

Positive100%

Neutral0%

Negative0%

Candidates reported having very good feelings for Meta's Software Engineer - Machine Learning interview process in California City, California.

Meta Work Experiences

PSC is stressful

Software Engineer - Machine Learning • Current Employee

San Francisco, California, United States

Pros: Top of market pay, and it seems like people who work here do care about the money.

Cons: As an MLE, delivery impact each half is stressful and unrealistic. PERM's high failure rate is hard for H1B holders.

PSC is stressful

Software Engineer - Machine Learning • Current Employee

San Francisco, California, United States

Pros: Top of market pay, and it seems like people who work here do care about the money.

Cons: As an MLE, delivery impact each half is stressful and unrealistic. PERM's high failure rate is hard for H1B holders.

Limited Growth, Poor Environment

Software Engineer - Machine Learning • Current Employee

Menlo Park, California, United States

December 23, 2024

Pros: Lots of GPU In-house LLM for any use

Cons: Some orgs like to adopt a zero-sum working atmosphere and like to compare people. It is hard to have technical advancement given everyone is chasing lower-hanging fruit. Low hourly pay.

Limited Growth, Poor Environment

Software Engineer - Machine Learning • Current Employee

Menlo Park, California, United States

December 23, 2024

Pros: Lots of GPU In-house LLM for any use

Cons: Some orgs like to adopt a zero-sum working atmosphere and like to compare people. It is hard to have technical advancement given everyone is chasing lower-hanging fruit. Low hourly pay.

Good pay and benefits. Nothing else

Software Engineer - Machine Learning • Current Employee

Menlo Park, California, United States

Pros: Good pay and benefits package. Love the food.

Cons: Bad work-life balance, and it can be hard to ramp up to the culture.

Good pay and benefits. Nothing else

Software Engineer - Machine Learning • Current Employee

Menlo Park, California, United States

Pros: Good pay and benefits package. Love the food.

Cons: Bad work-life balance, and it can be hard to ramp up to the culture.

PSC is stressful

Software Engineer - Machine Learning • Current Employee

San Francisco, California, United States

Pros: Top of market pay, and it seems like people who work here do care about the money.

Cons: As an MLE, delivery impact each half is stressful and unrealistic. PERM's high failure rate is hard for H1B holders.

3.0
PSC is stressful
Software Engineer - Machine Learning • Current Employee
San Francisco, California, United States
April 29, 2025
Pros: Top of market pay, and it seems like people who work here do care about the money.
Cons: As an MLE, delivery impact each half is stressful and unrealistic. PERM's high failure rate is hard for H1B holders.

Limited Growth, Poor Environment

Software Engineer - Machine Learning • Current Employee

Menlo Park, California, United States

December 23, 2024

Pros: Lots of GPU In-house LLM for any use

Cons: Some orgs like to adopt a zero-sum working atmosphere and like to compare people. It is hard to have technical advancement given everyone is chasing lower-hanging fruit. Low hourly pay.

1.0
Limited Growth, Poor Environment
Software Engineer - Machine Learning • Current Employee
Menlo Park, California, United States
December 23, 2024
Pros: Lots of GPU In-house LLM for any use
Cons: Some orgs like to adopt a zero-sum working atmosphere and like to compare people. It is hard to have technical advancement given everyone is chasing lower-hanging fruit. Low hourly pay.

Good pay and benefits. Nothing else

Software Engineer - Machine Learning • Current Employee

Menlo Park, California, United States

Pros: Good pay and benefits package. Love the food.

Cons: Bad work-life balance, and it can be hard to ramp up to the culture.

5.0
Good pay and benefits. Nothing else
Software Engineer - Machine Learning • Current Employee
Menlo Park, California, United States
April 24, 2023
Pros: Good pay and benefits package. Love the food.
Cons: Bad work-life balance, and it can be hard to ramp up to the culture.

Meta Interview Questions

Minimum Remove to Make Valid Parentheses

Given a string with parentheses, determine the minimum number of parentheses you must remove to make the string valid. A valid string has balanced and properly nested parentheses.

StringsStacksTwo Pointers

Valid Word Abbreviation

Determine if a given abbreviation is valid for a given word. An abbreviation can contain digits representing the number of skipped characters.

StringsTwo Pointers

Binary Tree Vertical Order Traversal

Traverse a binary tree and return a list of node values for each vertical line, ordered from left to right. Nodes on the same vertical line should be ordered from top to bottom.

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