Bloom Energy Machine Learning / Data Science Intern �
San Jose, CA·43 interview reviews·Medium difficulty
Machine Learning / Data Science Intern � Interview Reviews
43The process was pretty straightforward. It started with an online assessment, followed by a phone screen, and concluded with a final interview round that had two LeetCode medium difficulty problems.
“LRU Cache - Design a data structure for Least Recently Used cache”
Just one round with 2 LC hards in 45 min. It wasn't too bad at all — if you've done a lot of LC you're gonna be fine. Make sure to check off your approach with the interviewer before you begin implementing.
“Clone Graph - Create a deep copy of an undirected graph”
CodeSignal online assessment, then one 45-minute interview. Interviewer was friendly and helpful. 2 leetcode questions then 5 minutes for any questions I had. Got my results in a few days.
“Describe a time when you had to learn something quickly to complete a project”
Applied online and heard back in about a week. The technical interview was 45 minutes with two coding problems. Focus on time complexity and edge cases. The behavioral portion was brief but important.
“Design Web Crawler - Design a distributed web crawling system”
About This Role
Frequently Asked Questions
How hard is it to get hired as a Machine Learning / Data Science Intern � at Bloom Energy?
The interview difficulty is rated 3.3/5 by candidates. 64% report a positive experience. Focus on Machine Learning, Python, Statistics to improve your chances.
How long does the Bloom Energy Machine Learning / Data Science Intern � hiring process take?
The process typically takes 2–6 weeks from application to final decision, depending on the hiring cycle and team availability.
What is the interview process like?
Most candidates go through a recruiter screen, followed by technical coding rounds, and a final interview loop. 51% of candidates applied online.
What questions are asked in a Bloom Energy Machine Learning / Data Science Intern � interview?
Common topics include data structures & algorithms (arrays, trees, graphs), system design, and behavioral questions using the STAR method. Practice with our AI mock interviewer to prepare.
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