xAI interview notes, page 9 of 9

Mid-sized

Most of these xAI write-ups come from Software Engineers (74), then Machine Learning Engineers (11) and Backend Engineers (1). The most reported rounds are the technical phone screen (52), the system design round (12), the behavioral / leadership round (6) and the onsite coding round (4).

86 interview notes · updated Jul 2026

xAI·Software Engineer·Hiring Manager Screen

Jun 2026

Behavioral round at xAI that was basically a rapid-fire interrogation of your resume. The interviewer zeroed in on your best project and just kept drilling. Fast paced and a bit relentless.

Walk me through your most impressive project. What was the problem you were solving?
Why is this project technically impressive? What makes it stand out?
What specifically did you contribute versus the rest of the team?
What were the key technical decisions you made, and what trade-offs did you consider?
Looking back, what would you do differently on that project?
What was the measurable impact of your work on this project?

“You really need to have one project locked and loaded before this conversation.”

View Post

xAI·Software Engineer·Technical Phone Screen

Jun 2026

Interviewed for a software engineer role at xAI. Pretty standard intro round, just one question but it was open enough that you could sink or swim depending on what project you picked.

Walk me through your background, then describe the most interesting project you've worked on. Make sure it's relevant to what this team does, and cover what made it interesting, what you personally did, and what the outcome was.

“The open-endedness of this tripped me up a bit.”

View Post

xAI·Software Engineer·Recruiter / HR Screen

Jun 2026

Screened for a software engineer role at xAI and the conversation zeroed in pretty quickly on motivation and fit rather than pure technical stuff. One question in particular required some real prep to answer well.

What specifically do you want to work on at xAI, and why? Walk us through which teams or projects interest you, how that connects to the company's mission, and why your background makes you a good fit.

“This tripped me up more than I expected.”

View Post

xAI·Machine Learning Engineer·Technical Phone Screen

Jul 2026

Interviewed for an ML Engineer role at xAI and got a pretty deep systems-level coding question about building a batched inference engine from scratch. Not your typical LeetCode session, more like a mini-project scoped to an hour.

Design and implement a dynamic batching decoding engine for a black-box language model interface. The engine should manage a fixed-capacity batch, pull from a waiting queue to fill open slots, handle per-sequence stopping conditions (both a single stop token and a stop sequence suffix), respect per-request token limits, and correctly map batch slots to requests so outputs never get mixed up when slots are refilled.

“This one took me a minute to even parse.”

View Post

xAI·Software Engineer·Online Assessment (OA)

Jul 2026

xAI SWE interview had me building an in-memory database from scratch across four progressive levels, starting with basic CRUD and ending with TTL expiry and backup/restore logic. It was a single coding round and the problem kept stacking requirements on top of itself, which was the whole point.

Implement basic CRUD operations (set, get, delete) on fields within keyed records in an in-memory database.
Add scan and scan-by-prefix operations that return all fields (or prefix-matching fields) for a given key, formatted as 'field(value)' and sorted lexicographically.
Extend the database with timestamped versions of all operations, including a set_at_with_ttl that makes a field expire at timestamp + ttl (half-open interval).
Implement backup and restore: backup captures a snapshot at a given timestamp (storing remaining TTL for fields), and restore reinstates the latest backup at or before a target time, recalculating expiry relative to the restore timestamp.

“This part was fine.”

View Post

xAI·Software Engineer·Technical Phone Screen

Jul 2026

xAI software engineer technical screen, one coding problem the whole time. Classic phone keypad encoding thing, looked familiar but the trie angle tripped me up a bit.

Given a dictionary of words and a list of digit-string queries, return all dictionary words whose phone keypad encoding starts with each query, sorted lexicographically. Each digit 2-9 maps to a group of letters the way old T9 phones worked.

“My first instinct was to just encode every word upfront and then for each query do a prefix scan.”

View Post