Rippling Phone Interview
- Posted
- 25 Feb 2026
Summary
I had a phone interview with Rippling where I was presented with two coding questions related to calculating employee pay, including a part on hourly payouts with time constraints and caching. The process was negatively impacted by an unreliable recruiter.
How it went
For starters use an LLM. I was told there would be two different questions depending on if you use an LLM, that is a lie.
You're given a list of doordash employees that make a certain amount per hour as well as how long they work.
Part 1: Create a function to compute the total amount of money all the dashers make
Part 2: You now want to pay these door dashers by the hour. Add a new function so you can pay people hourly. I.e if i'm working 12-10pm and we want to pay all dashers that have worked before 5pm, this dashers pay should be included. Also consider how you can cache this info instead of repeating
Overall the recruiter was incredibly unreliable and made this process more difficult than needed to be
Questions asked (2)
- 01
Calculate Total Employee Pay
Data Structures & Algorithms · Easy
Given a list of employees, each with an hourly rate and hours worked, create a function to compute the total amount of money all the employees make.
- 02
Hourly Payout with Time Constraint and Caching
Data Structures & Algorithms · Medium
Expand on the previous problem. Add a new function to pay employees hourly based on a specific time constraint. For example, if an employee worked 12 PM - 10 PM and we want to pay all employees who worked before 5 PM, this employee's pay for hours worked before 5 PM should be included. Also, consider how to cache this information to avoid redundant computations.