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Grammarly Interview Questions (30)

Coding problems reported from Grammarly interviews and online assessments.

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A private sheet of Grammarly's most asked problems with a two-week finish date.
Questions30
Easy7
Medium19
Hard4
Asked in 30 days5as of 16 Aug 2026
TitleSolutionAcceptDifficultyAsked
Solution64.0%Medium
Last 30 days
Solution52.1%Easy
Last 30 days
69. Sqrt(x)Video
Solution42.2%Easy
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More about Grammarly interviews

Grammarly is known for building large-scale AI and NLP systems that help millions of users improve their writing in real time. Because their product relies heavily on efficient text processing and high‑performance services, Grammarly’s engineering interviews emphasize strong fundamentals in data structures and algorithms along with practical problem‑solving skills.

The typical Grammarly coding interview evaluates how well you design clean solutions, reason about edge cases, and communicate your thinking. Candidates are usually asked to solve algorithmic problems similar to those found on top coding platforms but often framed around string processing, data handling, or real‑world product scenarios.

From analyzing real interview experiences, most Grammarly coding questions fall into a few recurring patterns:

  • String manipulation and text processing problems
  • Hash maps and frequency counting for efficient lookups
  • Sliding window and two‑pointer techniques
  • Trees and graph traversal for structured data problems
  • Dynamic programming for optimization scenarios

The difficulty distribution is typically balanced: candidates encounter a mix of easy warm‑up problems, medium‑level algorithm challenges, and occasionally a harder optimization question. Interviewers care less about memorized tricks and more about how you break down problems and iterate toward better solutions.

On FleetCode, we’ve curated reported by candidates and organized them by difficulty. Each problem includes explanations and implementations in Python, Java, and C++, helping you practice the exact patterns Grammarly tends to test. If you want to prepare efficiently and understand how Grammarly evaluates engineers, these problems give you a focused path to mastering their coding interview.

Interview tips

Preparing for a Grammarly coding interview requires a strong grasp of algorithm fundamentals and the ability to clearly explain your reasoning. While the exact format may vary by role and location, the process usually follows a structured set of technical rounds.

Typical Grammarly interview process:

  • Recruiter screen (30 minutes): Discussion about your background, projects, and motivation for joining Grammarly.
  • Technical phone screen (45–60 minutes): One or two coding problems solved in a shared editor. Interviewers evaluate problem‑solving approach, code clarity, and time complexity.
  • Onsite or virtual onsite (3–4 rounds): Includes multiple coding interviews, a system design discussion for experienced roles, and a behavioral or collaboration round.

Across these rounds, Grammarly tends to focus on a few core algorithm categories:

  • Strings and text processing: substring problems, pattern matching, and transformations
  • Hash tables and counting: frequency maps and deduplication logic
  • Sliding window and two pointers: especially for substring or sequence problems
  • Trees and graphs: traversal, BFS/DFS, and hierarchical structures
  • Dynamic programming: optimization problems involving sequences or edits

Preparation strategy: Start with array, string, and hash map problems because they appear frequently in Grammarly interviews. Then practice sliding window and tree traversal patterns. Finally, add dynamic programming and graph problems to handle harder rounds. Aim to solve problems while explaining your thought process out loud, since communication is a key evaluation factor.

Common mistakes to avoid:

  • Jumping straight into coding without discussing the approach
  • Ignoring edge cases such as empty strings or large inputs
  • Writing complex code instead of a clean, readable solution
  • Forgetting to analyze time and space complexity

Recommended timeline: Most candidates prepare for 4–8 weeks. Working through a curated set of real Grammarly interview questions, like the , helps you focus on the patterns most likely to appear in the actual interview.

Frequently asked questions

What DSA topics does Grammarly ask most?

Common topics include strings, hash maps, sliding window techniques, arrays, and tree or graph traversal. Because Grammarly builds writing and language tools, string manipulation and text-processing problems appear frequently. Dynamic programming and optimization problems may appear in later rounds.

How hard are Grammarly coding interviews?

Grammarly coding interviews are generally considered medium difficulty. Most problems are comparable to medium-level LeetCode questions, with occasional harder follow-ups. Interviewers focus on problem-solving clarity, efficient algorithms, and clean code rather than tricky puzzles.

Does Grammarly ask system design questions?

Yes, system design questions are often included for mid-level and senior engineering roles. These interviews may focus on designing scalable services, text-processing systems, or real-time APIs similar to Grammarly’s product architecture.

What is the Grammarly interview process like?

The process usually starts with a recruiter screen followed by a technical phone interview with coding questions. Candidates who pass are invited to a virtual or onsite interview with multiple coding rounds, and sometimes a system design discussion for experienced engineers. Behavioral evaluation and collaboration skills are also assessed.

How many LeetCode problems should I solve for Grammarly?

Focus on medium-level problems and pattern recognition rather than solving thousands of random questions.

How long should I prepare for a Grammarly coding interview?

A typical preparation timeline is 4–8 weeks depending on your current DSA knowledge. Spend the first weeks strengthening fundamentals like arrays, strings, and hash maps, then practice more advanced topics such as graphs and dynamic programming while doing mock interviews.