Google, big tech & the AI labs

Scores four attributes - General Cognitive Ability, Role-Related Knowledge, Leadership, and "Googleyness" - with a dedicated behavioral round. Coding has historically been in a plain shared doc (no IDE, no autocomplete, no running code). System design appears at senior levels (roughly L5+). The hire decision is made by a hiring committee that never met you, decoupling it from any single interviewer.

Everything maps to the 16 Leadership Principles; most rounds include behavioral questions you answer in STAR format (Situation, Task, Action, Result). The loop includes a Bar Raiser - a trained interviewer from outside the team with effective veto over the offer. The online assessment pairs coding with a work-simulation component.

A typical onsite is two coding rounds, one design round (System Design for infra, Product Architecture for product), and one behavioral. Coding rounds are known for expecting about two problems in a short window. Meta has reportedly begun piloting an AI-enabled coding round (late 2025) alongside a traditional AI-free algorithm round.

Hires team-by-team, so format and content vary a lot by organization. Team fit is built into the process rather than a separate step after the offer - you interview for a specific team.

Recruiter screen, an online coding assessment or phone screen, an onsite loop of about three to five interviews, then team matching once you pass the loop.

Less standardized than big tech. Expect more machine-learning depth, a discussion of your own research or projects, ML/AI-infrastructure system design, and mission or safety-alignment conversations. Research and research-engineer roles often add a take-home. Automated screens like CodeSignal appear (Anthropic, Meta).

Hires domain specialists: strong C++ and CUDA for systems roles, framework internals for ML roles. Even coding rounds probe performance - memory, latency, throughput.

Coding & algorithms

Data structures and algorithms under time pressure: arrays and hash maps, two pointers, sliding windows, stacks/queues, trees and graphs (BFS/DFS), heaps, and dynamic programming. Remember the constraints - a plain doc at Google, about two problems per round at Meta. This is the round EcoFinLearn does not drill; use it for the Python foundation, then grind patterns on NeetCode.

System design

Design a large system out loud: the building blocks and trade-offs below. Mostly asked at senior levels, but worth learning early - it is what separates strong candidates. This is where a data / backend background pays off.

Behavioral & leadership

Prepared stories in STAR format, mapped to what each company scores - Amazon's 16 Leadership Principles, Google's Leadership and "Googleyness", Meta's values. Have 6-8 concrete stories (a conflict, a failure, an ambiguous problem you drove) ready to reshape on the fly.

Do I need a CS degree from a top school?

It helps for getting the interview, but the loop is a skills test: coding, system design and behavioral. Plenty of people convert from other backgrounds with demonstrable, shipped work. What gates you is the bar, not the crest on your diploma.

Is 2026 a bad time to try?

It is a harder, more selective time, and entry-level is squeezed the most - but hiring is concentrated, not frozen, and it is concentrated exactly in AI/ML, infrastructure and security. Depth in those areas is worth more now than it was in 2021.

Do I really have to grind LeetCode?

For the coding rounds, largely yes - but grind patterns, not problems. A few hundred well-chosen problems (e.g. NeetCode 150) that teach the recurring patterns beats thousands done blindly.

When does system design actually matter?

Mostly from senior level up (roughly Google L5, Meta E5). But learning it early is the highest-leverage differentiator, and it is the round where a data or backend background shines.

Can I use AI assistants (Copilot, ChatGPT) in the interview?

It depends on the round and is changing fast - Meta is piloting an AI-enabled coding round, while most algorithm rounds are still AI-free. Always confirm the rules with your recruiter before each round. The skill now being tested is judging and validating code, not just producing it.

Big tech or an AI lab?

AI labs (OpenAI, Anthropic, DeepMind) pay at the very top and want ML depth, your own research and safety-minded thinking; big tech is more standardized and hires at more levels. Neither is easy - pick by the work you want to do.

I am in Europe or India - is the pay the same?

No. The US figures here skew high; senior pay in Germany is roughly $85K–125K equivalent, and India is far lower. If you are targeting India specifically, see the dedicated India guide.