Bloomberg LP

Machine Learning Engineer Interview Experience - United States

August 5, 2023

Neutral ExperienceNo Offer

Process

A very pleasant experience.

However, the quality of the interviewers was low. They asked some questions about transformers, and it is obvious that they do not know what they are asking about.

The coding question was asinine and nonsensical. For sure, they need to take interviewing more seriously.

Questions

Overview of Transformers.
Some coding question about a stream of chat messages and a sliding window. (Badly presented)

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Interview Statistics

The following metrics were computed from 7 interview experiences for the Bloomberg LP Machine Learning Engineer role in United States.

Success Rate

14%

Pass Rate

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

Experience Rating

Positive71%

Neutral29%

Negative0%

Candidates reported having very good feelings for Bloomberg LP's Machine Learning Engineer interview process in United States.

Bloomberg LP Work Experiences

Supportive to personal growth

Machine Learning Engineer • Current Employee

Pros: - Flat structure that makes it easy to get buy-in for new ideas. - Open and collaborative colleagues that you can learn from. - Opportunities for personal growth.

Cons: - Investing more time pays off (product impact, personal growth), so it’s easy to lose track of work/life balance if you aren’t careful.

Supportive to personal growth

Machine Learning Engineer • Current Employee

Pros: - Flat structure that makes it easy to get buy-in for new ideas. - Open and collaborative colleagues that you can learn from. - Opportunities for personal growth.

Cons: - Investing more time pays off (product impact, personal growth), so it’s easy to lose track of work/life balance if you aren’t careful.

Great Balance, Too Many Meetings

Machine Learning Engineer • Current Employee

New York, New York, United States

Pros: Great work-life balance, great perks including health/dental/vision insurance with no monthly premiums for employees and their children, access to pretty much every museum in NYC, and decent PTO (4 weeks). The company isn't owned by shareholders, which helps with the culture and long-term vision. There are no layoff/PIP quotas. Virtually all profits produced by Bloomberg LP go to charity.

Cons: There are too many meetings.

Great Balance, Too Many Meetings

Machine Learning Engineer • Current Employee

New York, New York, United States

Pros: Great work-life balance, great perks including health/dental/vision insurance with no monthly premiums for employees and their children, access to pretty much every museum in NYC, and decent PTO (4 weeks). The company isn't owned by shareholders, which helps with the culture and long-term vision. There are no layoff/PIP quotas. Virtually all profits produced by Bloomberg LP go to charity.

Cons: There are too many meetings.

Interesting Work, Good Pay

Machine Learning Engineer • Current Employee

New York, New York, United States

Pros: Interesting work. Financial. Good pay.

Cons: Not too many. Overall good.

Interesting Work, Good Pay

Machine Learning Engineer • Current Employee

New York, New York, United States

Pros: Interesting work. Financial. Good pay.

Cons: Not too many. Overall good.

Supportive to personal growth

Machine Learning Engineer • Current Employee

Pros: - Flat structure that makes it easy to get buy-in for new ideas. - Open and collaborative colleagues that you can learn from. - Opportunities for personal growth.

Cons: - Investing more time pays off (product impact, personal growth), so it’s easy to lose track of work/life balance if you aren’t careful.

5.0
Supportive to personal growth
Machine Learning Engineer • Current Employee
July 25, 2024
Pros: - Flat structure that makes it easy to get buy-in for new ideas. - Open and collaborative colleagues that you can learn from. - Opportunities for personal growth.
Cons: - Investing more time pays off (product impact, personal growth), so it’s easy to lose track of work/life balance if you aren’t careful.

Great Balance, Too Many Meetings

Machine Learning Engineer • Current Employee

New York, New York, United States

Pros: Great work-life balance, great perks including health/dental/vision insurance with no monthly premiums for employees and their children, access to pretty much every museum in NYC, and decent PTO (4 weeks). The company isn't owned by shareholders, which helps with the culture and long-term vision. There are no layoff/PIP quotas. Virtually all profits produced by Bloomberg LP go to charity.

Cons: There are too many meetings.

5.0
Great Balance, Too Many Meetings
Machine Learning Engineer • Current Employee
New York, New York, United States
April 29, 2024
Pros: Great work-life balance, great perks including health/dental/vision insurance with no monthly premiums for employees and their children, access to pretty much every museum in NYC, and decent PTO (4 weeks). The company isn't owned by shareholders, which helps with the culture and long-term vision. There are no layoff/PIP quotas. Virtually all profits produced by Bloomberg LP go to charity.
Cons: There are too many meetings.

Interesting Work, Good Pay

Machine Learning Engineer • Current Employee

New York, New York, United States

Pros: Interesting work. Financial. Good pay.

Cons: Not too many. Overall good.

4.0
Interesting Work, Good Pay
Machine Learning Engineer • Current Employee
New York, New York, United States
April 22, 2024
Pros: Interesting work. Financial. Good pay.
Cons: Not too many. Overall good.

Bloomberg LP Interview Questions

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.

Subsets

Given a set of distinct integers, your task is to generate all possible subsets (the power set). The solution should not contain duplicate subsets.

ArraysRecursionBit Manipulation

Longest Substring Without Repeating Characters

Find the length of the longest substring within a given string that contains no repeating characters. The substring must be contiguous.

StringsTwo PointersSliding Windows

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