Went through the Scale AI software engineer interview process start-to-finish last month for a senior backend role. Here's the full loop so you know what you're signing up for.
Recruiter screen (30 min). Standard stuff. They want to know your background, why Scale, and if you've worked on data-heavy or AI infrastructure systems. Nothing technical yet, but the recruiter did ask about scope and impact in prior roles, so have a concise story ready.
Technical phone screen (60 min). One coding problem, Leetcode medium difficulty. Mine was a graph traversal variant. The interviewer shared a Coderpad link. Expect a back-and-forth on time/space complexity and a follow-up question that extends the original problem.
Take-home or async OA. Not everyone gets this. Some candidates go straight to onsite. I got a short async assessment through Hackerrank, two problems, 90 minutes. Both were medium-level algorithmic coding, nothing domain-specific.
Onsite (virtual, 4-5 rounds). This is where it gets real: Two coding rounds. Leetcode medium-hard range. One of mine touched string manipulation and the other was a DP problem. One system design round. They're interested in distributed systems, data pipelines, and scale (fitting, given the company). Think along the lines of designing a large-scale labeling pipeline or annotation queue. Concretely: you'll need to discuss throughput, latency tradeoffs, storage, and fault tolerance. One behavioral round. See the separate thread on this. Sometimes a bar-raiser or second design round at senior level.
Timeline. Recruiter screen to onsite took about 2.5 weeks for me. Offer decision came back in 5 business days post-onsite.
Overall, the process is rigorous but not adversarial. The interviewers were engaged and asked clarifying questions if I got stuck rather than just watching me flounder. Leveling felt accurate to what I'd expect at a Series B/C-adjacent AI company that's now operating at real scale.
Happy to answer specifics below.