Instacart interview notes, page 1 of 13

Large Enterprises

Most of these Instacart write-ups come from Software Engineers (88), then Data Scientists (28) and Machine Learning Engineers (5). The most reported rounds are the technical phone screen (93), the system design round (13), the behavioral / leadership round (6) and the product sense round (6).

128 interview notes · updated Jul 2026

Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Instacart coding screen with a pretty niche problem around temporal task tracking. Not your typical array or graph question, more of a data modeling puzzle with some simulation logic baked in.

Design and implement a function that, given a simulation timestamp and a user ID, returns the number of tasks assigned to that user which were active as of a specified historical point in time.

“The bi-temporal angle is what trips you up if you're not expecting it.”

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Instacart·Machine Learning Engineer·Technical Phone Screen

Apr 2026

ML concepts interview for a machine learning engineer role at Instacart. Two meaty theory questions, both pretty fundamental but they clearly wanted depth not just definitions.

Walk me through the differences between linear regression and logistic regression, including when you'd use each, how the models are formulated, what loss functions they use, and how you'd interpret the coefficients.
Explain the bias-variance tradeoff. How do model complexity, training data size, and regularization each affect it, and what techniques would you use to manage it in practice?

“Knew this cold or thought I did.”

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Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Instacart SWE interview with a coding question that looks deceptively simple but has a parity edge case that'll trip you up if you're not paying attention. The O(n) constraint is the real test here.

Given an integer array that may include negative numbers, count all contiguous subarrays where the elements strictly alternate between odd and even parity. Subarrays of length 1 always qualify. Can you do it in O(n)?

“The negative number thing is where I fumbled first.”

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Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Instacart coding round that extended a task manager system with user management and a scheduled deletion feature. The scheduling constraint was the tricky part.

Extend a task manager class with addUser, assignTaskToUser, unassignTaskToUser, and a scheduleDeletion method that deletes a task after a given delay from a timestamp. Scheduled deletions must be processed before any other operation at the same timestamp.

“The first three methods were fine, pretty much just bookkeeping with maps.”

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Instacart·Product Manager·Onsite - Product Sense / Strategy

Apr 2026

PM interview at Instacart with a product metrics question about Google Flight Search. Short session, one question, left me second-guessing my framework the whole way home.

How would you define success metrics for Google Flight Search?

“I jumped straight to booking conversion and kind of forgot that search itself has its own success story separate from whether someone actually buys a ticket.”

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Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Coding screen for a software engineer role at Instacart. One algorithmic string manipulation question, pretty focused, nothing too wild but it had a few edge cases that could trip you up if you rushed.

Given an array of strings, for each string check if both the first and last characters are vowels (case-insensitive). If they are, reverse everything between the first and last characters and return the modified array. If not, leave the string as-is.

“Took me a minute to realize 'middle portion' meant indices 1 through len-2, not some fuzzy definition.”

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Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Instacart SWE interview via Karat, building on a sports-stats coding problem from a prior round. The follow-up asked me to extend the solution I'd already written, which sounds easier than it is when you're mid-session and second-guessing your earlier code.

Given a 2D structure where rows are athletes and columns are events, implement a function that returns the single best score for a specific event across all athletes. For each athlete, consider only their completed attempts and take their highest score, then return the maximum of those across all athletes.

“The tricky part wasn't the logic, it was that this was a continuation problem.”

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Instacart·Backend Engineer·Onsite - System Design / Architecture

Apr 2026

Instacart backend design round, pretty intense. The whole session was focused on a single inventory management problem and they wanted real depth on schema and concurrency, not hand-wavy stuff.

Design an inventory management system for an e-commerce or warehouse context, with no caching layer. All reads and writes go directly to the relational database.
Walk through your database schema for this system. What tables do you create, what are the primary keys and indexes, and how do you enforce constraints?
How do you handle concurrency and prevent overselling without using a cache? What locking strategy do you use?
Design the API surface for this system. What endpoints do you expose, what do the request and response shapes look like, and how do you handle idempotency?
How would you use the stock movement ledger for reconciliation and auditing? Can you reconstruct current stock levels from it?
What are the throughput limits of this pure-DB approach and how would you scale the read and write paths while staying cache-less?

“This was the whole interview basically.”

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Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Interviewed for a bizops role at Instacart and got a SQL question that seemed straightforward but required some careful thinking about how the data was structured across zip codes.

Write a SQL query to sum the total number of rides and deliveries completed, grouped by zip code, using the provided dataset.

“Felt pretty comfortable with the aggregation part but spent a weird amount of time second-guessing whether to use a single SUM with a CASE statement or two separate columns.”

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Instacart·Software Engineer·Technical Phone Screen

Apr 2026

Instacart SWE interview with a pretty involved coding problem around log parsing and priority queues. The follow-up on heap optimization is what made it interesting, and honestly a bit stressful in the moment.

You have a folder of log files where each line is a bus event. Parse the logs to reconstruct a schedule: for each bus ID, list its arrival times at each stop.
Using the parsed schedule, implement priority boarding: riders at each stop have a priority score, and when a bus arrives, board them in priority order (highest first) up to the bus's remaining capacity. Riders who don't board stay in the queue for the next bus.
You sorted the waiting list on each bus arrival, which is O(n log n) per arrival. How would you improve this, and can you implement a heap-based version? Walk through the complexity.

“The parsing part felt manageable.”

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