AI Labs vs Big Tech: Who Has the Hardest Interviews?

The comparison covers the frontier labs against the seven largest tech employers, with difficulty weighted by report volume. Method at the end.

The difficulty column is almost flat: rows 1 through 12 sit between 3.12 and 3.35. Now read the offer-rate column and the two groups pull apart. Big Tech rows show 16% to 35%. AI lab rows show 4% to 23%, with Groq the only lab above 25% and on a sample of 53. The positive-experience column tells the same story: Big Tech 54% to 66%, the labs 27% to 58%. Pay runs the other way, with four of the five highest medians belonging to labs. The labs are not harder. They are more selective and less pleasant about it.

Read the two groups side by side and the pattern is consistent. Big Tech runs a hard loop and then makes a decision: Amazon converts 35%, Microsoft 32%, Apple 29%. The labs run a loop of the same difficulty and convert 4% to 23%. For a candidate, that means the same preparation buys very different odds, and the low positive-experience rates at OpenAI and Anthropic suggest a lot of that gap is silence rather than a no.

Filtering to specific roles with 10 or more reports, the labs take the top three.

Machine Learning Engineer is the role that separates the two camps most. Anthropic MLE 4.00, OpenAI MLE 3.89, then Meta MLE 3.38, Google MLE 3.27, Apple MLE 3.08, Amazon MLE 2.65. That is a 1.35-point spread on one title. Software Engineer is far tighter: Databricks 3.45, Google 3.43, Anthropic 3.40, Meta 3.39, OpenAI 3.34, Amazon 3.32, xAI 3.30, all within 0.15 of each other. If you are interviewing for SWE, the brand matters less than you think. If you are interviewing for MLE, it matters a lot.

Two rows to sit with. Microsoft Machine Learning Engineer: 3.40 difficulty, the same as Anthropic Software Engineer, and a 60% offer rate against 6%. And Amazon Machine Learning Engineer at 2.65, the easiest ML loop among the fourteen companies, a full 1.35 points below Anthropic for the same title.

Interview reports are candidate-submitted interview experiences in Dataford's pipeline (Glassdoor, Blind, LeetCode and other sources). Difficulty is 1 (very easy) to 5 (very difficult); 3 is average. Experience is the share of reports marked positive or negative. Offer rate counts only reports that were fully parsed; companies whose reports carry no offer information at all are excluded from offer rankings.

Employee ratings for work-life balance, career opportunities, management and overall are 1 to 5. Where a company has 500+ Glassdoor reviews in its aggregate profile that figure is used; otherwise Dataford's own scraped review sample (100+ reviews). Pay is the company median across tech-role pay bands: leveled total-comp ladders where published, otherwise best-supported posted ranges (15+ data points). Posted ranges understate equity-heavy packages.

Each ranking states its own threshold. Near-duplicate company names were merged and review-farm entries removed. Snapshot 4 September 2026. Built from internal data only.