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Anthropic interview notes, page 3 of 32

Mid-sized

Most of these Anthropic write-ups come from Software Engineers (277), then Machine Learning Engineers (31) and Product Managers (10). The most reported rounds are the technical phone screen (129), the system design round (86), the behavioral / leadership round (45) and the hiring manager screen (17).

319 interview notes · updated Sep 2026

Anthropic·Machine Learning Engineer·Onsite - System Design / Architecture

Apr 2026
Interviewed for an ML engineer role at Anthropic and got hit with a pretty open-ended system design question about building an agentic AI that can figure out new tasks on its own. Not a lot of constraints given upfront, which was either the point or just how they roll.
  • Design an agentic AI system that can autonomously adapt to new tasks it hasn't been explicitly trained for.

“This one is deceptively wide.”

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Anthropic·Software Engineer·Technical Phone Screen

Apr 2026
Anthropic coding interview that was more systems-thinking than I expected. The problem looked like a straightforward image processing exercise but they really wanted to see how you design a clean API and reason about trade-offs, not just grind out the pixel math.
  • Implement a set of image processing operations on a 2D pixel grid (box blur with a configurable kernel, horizontal and vertical flip, 90-degree rotation, brightness adjustment). Define a clean interface so operations can be chained or composed, and walk through the trade-offs between in-place and out-of-place execution.

“I jumped straight into writing the individual functions before thinking about the interface, which was the wrong move.”

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Anthropic·Machine Learning Engineer·Onsite - System Design / Architecture

Apr 2026
Anthropic ML engineer interview with a meaty systems question about weighted dataset batching. The problem kept evolving and I kept second-guessing my approach. Not sure how I did.
  • You have a DataBatcher that mixes multiple datasets according to weight ratios. Batch size is not guaranteed to be divisible by the sum of weights. How do you ensure each batch respects the proportions on average without drifting over time, and how do you make the whole thing deterministically resumable from an arbitrary offset?
  • What happens when one dataset has weight zero? How does your batching strategy handle that edge case?
  • What if the sum of weights is larger than the batch size, meaning you literally cannot include every dataset in a single batch? How do you rotate across datasets fairly?
  • Compare the carry-over fractional approach to a Bresenham-style precomputed emission schedule. What are the trade-offs?

“This is where I spent most of the interview.”

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Anthropic·Software Engineer·Hiring Manager Screen

Apr 2026
Interviewed for a software engineering role at Anthropic. The process covered the usual hiring manager territory plus a pretty heavy focus on AI safety thinking, which I expected but still found hard to nail concretely.
  • Walk me through your background and the projects you're most proud of.
  • Why do you want to join this team, and what do you see as your strengths and areas for growth?
  • Tell me about a time you took ownership of something ambiguous. How did you drive it forward?
  • How do you think about AI safety and responsible deployment in practice?
  • What guardrails and abuse-mitigation features would you build into an AI product you were shipping?
  • How would you evaluate and monitor model risks like prompt injection, jailbreaks, and data leakage? Give me a concrete example from something you've worked on.

“Standard opener but I rambled a bit.”

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Anthropic·Software Engineer·Online Assessment (OA)

Apr 2026
Anthropic coding assessment for what looks like a backend or software engineering role. Level 2 of a multi-level CodeSignal-style problem building a ChatBox Service, extending a Level 1 API with things like direct messages, channel membership, and message history. Pretty involved for an OA.
  • Extend a Level 1 ChatBox Service API to support additional operations including direct messaging, channel membership management, and querying message history.

“This is a build-on-top problem, so if your Level 1 was messy you'll feel it immediately.”

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Anthropic·Software Engineer·Recruiter / HR Screen

Apr 2026
Interviewed for a PMM role at Anthropic. Just one question to go off of here, but it was a pretty standard screen vibe.
  • How do you keep up with what's happening in marketing right now?

“Blanked for a second because I expected something more strategic first.”

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Anthropic·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Anthropic ML Engineer interview hit me with a deep-dive trie implementation question that went way beyond just writing the basic data structure. They wanted the full picture: complexity analysis, Unicode support, thread safety, trade-offs, the works.
  • Implement a prefix tree (trie) with insert, search, startsWith, countPrefix, and erase operations. Discuss time and memory complexity for each, handle Unicode characters, address thread-safety, outline test cases including edge cases, and compare the trade-offs against alternative data structures.

“This started as a trie question and turned into basically a systems design conversation about string indexing.”

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Anthropic·Software Engineer·Technical Phone Screen

Apr 2026
Phone screen for a software engineer role at Anthropic. One coding question involving image processing, felt a bit rushed but got through it and passed.
  • Given a set of images, write a solution to process them (grayscale conversion, scaling, resizing) first for small images, then extend it to handle large images efficiently.

“Time was tight and I wasn't moving fast enough, the interviewer had to nudge me along a couple times which was a little embarrassing.”

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Anthropic·Software Engineer·Hiring Manager Screen

Apr 2026
Interviewed for a SWE role at Anthropic and got asked something I wasn't fully prepared for about their actual direction as a company.
  • Do you have any critiques or concerns about Anthropic's approach or direction as a company?

“This one threw me a little.”

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Anthropic·Software Engineer·Technical Phone Screen

Apr 2026
This was a coding round for a recipe service problem, specifically the second level of a multi-part design. The core task sounds straightforward but the edge cases are where they actually test you.
  • Implement a function that returns chefs sorted by their accumulated recipe ratings, handling ties, chefs with no ratings, chefs with zero recipes, and case-insensitive name comparisons.

“I got the happy path working fast and felt good about it, then they started asking about ties.”

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