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Peloton Interviews

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Peloton Senior SDE Interview
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Peloton
Senior SDERejected
May 26, 20233 reads

Summary

I interviewed for a Senior SDE role at Peloton, which involved a phone screen followed by a comprehensive onsite interview. Despite my efforts, I ultimately received a rejection, which they attributed to the highly competitive nature of the process.

Full Experience

It's been a few months since my interview process with Peloton, but I wanted to share my experience here.

I initially received an invite for a recruiter call, which then led to a phone screen. The phone screen included a question focused on creating a data structure for reporting users.

Upon successfully passing the phone screen, I was invited for an onsite interview. I scheduled it with enough time to prepare adequately. The onsite interview was structured with several rounds:

  • Design Round: This round was specific to Peloton's domain, requiring system design relevant to their products.
  • Data Modeling Round: This was also a Peloton-specific question, focusing on how to model data for their systems.
  • Algorithms/Coding Round: This round had Peloton-specific elements but distinctly featured problems with characteristics of both merging schedules and skyline problems.
  • Behavioral Round: Standard behavioral questions were asked.

Unfortunately, I received a rejection letter, with the feedback indicating it was due to the competitive nature of the interviews.

Interview Questions (3)

Q1
Design Data Structure for User Reporting
Data Structures & Algorithms

During the phone screen, I was presented with a problem requiring the design and implementation of a data structure specifically tailored for reporting on user activities or attributes. The problem focused on optimizing for certain reporting queries or data access patterns, though the exact constraints are not fully recalled.

Q2
Algorithm Problem: Merging Schedules
Data Structures & Algorithms

In the algorithms round, one of the problems had core elements resembling classic 'merging schedules' or 'interval merging' problems. While the specific context was Peloton-related, the underlying algorithmic challenge involved efficiently combining or managing overlapping time intervals or events.

Q3
Algorithm Problem: Skyline Problem Variant
Data Structures & Algorithms

Another aspect of the algorithms round involved a problem that drew upon concepts found in 'the skyline problem'. It likely required calculating an outer contour or similar geometric/interval-based processing, adapted to a Peloton-specific scenario.

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