Salesforce Interview Questions — Page 10

Salesforce·Machine Learning Engineer·Hiring Manager Screen

Jun 2026

Salesforce MLE hiring manager round, 45 minutes, basically just a deep project walkthrough. You need real numbers and real decisions ready or you will get picked apart.

Walk me through a recent ML project. What was the business problem and what metric did you actually move?
For that project, what were your data sources, how did you engineer features, and how did you handle labeling?
Why did you choose that model over simpler alternatives? What tradeoffs did you weigh?
How did you evaluate the model offline and then validate it in production? What were the actual results?
After you shipped the model, how did you monitor it in production and what iterations did you do based on what you saw?

“This is where vague answers die.”

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Salesforce·Software Engineer·Onsite - System Design / Architecture

Jun 2026

System design round at Salesforce for a software engineer role, basically one big question about designing Dropbox from scratch. They wanted the full picture, not just storage, so be ready to go deep on sync protocols and conflict handling too.

Design a cloud file storage and synchronization service like Dropbox, covering upload/download, multi-device sync, file sharing, version history, and offline edits.
How would you design the chunk-based storage model with content-addressed deduplication?
Walk through the metadata service design, including the file tree structure, versioning, and permissions.
Describe the sync protocol end to end, from a local file change to all peer devices being updated.
How do you handle conflict resolution when two devices edit the same file offline and then sync?
How would you scale the storage and metadata layers across multiple geographic regions?

“I started with the functional requirements which felt right, but I spent way too long on the upload/download flow and barely had time for offline edits.”

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Salesforce·Software Engineer·Online Assessment (OA)

Jun 2026

Salesforce OA for a software engineer role, two coding problems. Nothing too wild but the second one had me second-guessing my approach the whole time.

Given an array of characters, compress consecutive runs of the same character in place. Write the character once, then the count as individual digit characters if the run is longer than one. Return the new length.
Given a positive integer n, find the minimum number of operations to reduce it to zero. If n is even, divide by 2. If n is odd, either add 1 or subtract 1.

“Two pointers ended up being the move here.”

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Salesforce·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026

Salesforce solutions architect interview with a classic market entry case. Not much else to say, it was a single strategic question and they let you run with it.

Should Amazon enter the food delivery market?

“I went straight to competitive landscape and kind of forgot to anchor on whether it even fits Amazon's core strengths first.”

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Salesforce·Product Manager·Hiring Manager Screen

Jun 2026

Interviewed at Salesforce, just one question about where the product falls short. Short and to the point, not much else to say.

What is one area where Salesforce could improve?

“I fumbled this a bit.”

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Salesforce·Software Engineer·Technical Phone Screen

Jun 2026

Salesforce SWE interview with a linked list problem. Pretty standard coding round, nothing too wild, but the in-place constraint is the kind of thing that trips you up if you're not paying attention.

Given the head of a singly linked list, remove all duplicate nodes in-place so only the first occurrence of each value remains, preserving the original order.

“My first instinct was a set to track seen values and just relink nodes as I walked the list.”

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Salesforce·Software Engineer·Technical Phone Screen

Jun 2026

Salesforce coding interview with a tricky string simulation problem. The naive approach works on small inputs but falls apart fast, and the interviewer clearly expected you to know that going in.

You have a binary string. Every second, all occurrences of '01' in the string simultaneously become '10'. This repeats until no '01' exists. How many seconds does the process take to complete?

“Started with the obvious simulation and coded it up cleanly, then they asked about performance on a long string and I kind of froze.”

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Salesforce·Software Engineer·Onsite - Coding / Algorithms

Jun 2026

Salesforce SWE onsite with two back-to-back segments: a CS/ML theory Q&A and then a live coding problem. The coding part was a full LFU cache implementation, not just a sketch, which I wasn't fully expecting.

Walk through CS and ML fundamentals. Expect theory questions covering core concepts from both areas.
Implement an LFU (Least Frequently Used) cache with get and put operations, both running in O(1) average time. You should use two hashmaps and a doubly linked list of frequency buckets.

“This part felt like a pop quiz with no clear scope.”

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Salesforce·Software Engineer·Online Assessment (OA)

Jun 2026

Salesforce OA for a software engineering role, structured as a code review exercise rather than typical leetcode. You get handed a set of Python backend files and have to write up at least ten review comments covering everything from security to schema design. Felt more like a real work task than an interview, which was kind of refreshing.

Review the provided Python backend code and identify at least 10 issues across different areas such as security, correctness, data modeling, concurrency, and reliability. For each issue, propose a concrete fix.
Identify any hardcoded secrets or credentials in the code and explain how you would remediate them.
Find SQL schema or query design problems in the code and suggest improvements.
Identify any race conditions or missing transactional safeguards in the database operations and describe how you would fix them.

“This was the whole OA basically.”

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Salesforce·Backend Engineer·Onsite - System Design / Architecture

Jun 2026

System design round at Salesforce for a backend engineer role, focused entirely on building the analytics backend for a ChatGPT-style product. No UI, no model internals, just the data pipeline and serving layer. Pretty meaty question that covered a lot of ground.

Design the analytics backend for a ChatGPT-like product. You need to cover what metrics to track, how to ingest data from upstream services, how to store and aggregate it, and how to serve dashboard queries efficiently.
How would you design the ingestion pipeline from upstream services like chat sessions, message-level events, and user accounts into your analytics store?
What slicing dimensions would you expose on the dashboard, and how do you handle the trade-off between query freshness and storage or compute cost?
How would you handle PII and data governance concerns in this analytics pipeline?

“This is a big open-ended question and I spent probably too long on the metrics enumeration part before getting to the architecture.”

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