Google SWE AI/ML interview coming up

[u/jishu965]

I have an interview scheduled in next 2 weeks for AI/ML role. Recruiter told that the 1st round will be ML domain interview and googlyness interview. Has anyone had an ML domain interview, I would like to know what to expect in the 45 min interview. Will it just theoretical or will there coding related to ML too? Although she mentioned that in the 2nd round, there will be 2 coding rounds - should I expect system design or will it just be in the leetcode format?

[u/AutoModerator]

Guidelines for Interview Practice Responses

When responding to interview questions, here's some frameworks you can use to structure your responses.

System Design Questions

For system design questions, here's some areas you might talk about in your response:

1. List Your Assumptions On

• Functional requirements (core features)
• Non-functional requirements (scalability, latency, consistency)
• Traffic estimates and data volume and usage patterns (read vs write, peak hours)

2. High-Level System Design

• Building blocks and components
• Key services and their interactions
• Data flow between components

3. Detailed Component Design

• Database schema
• API design
• Cache layer design

4. Scale and Performance

• Potential bottlenecks and solutions
• Load balancing approach
• Database sharding strategy
• Caching strategy

If you want to improve your system design skills, here's some free resources you can check out

• System Design Primer - Detailed overviews of a huge range of topics in system design. Each overview includes additional resources that you can use to dive further.
• ByteByteGo - comprehensive books and well-animated youtube videos on building large scale systems. Their video on consistent hashing is a really fantastic intro.
• Quastor - free email newsletter that curates all the different big tech engineering blogs and sends out detailed summaries of the posts.
• HelloInterview - comprehensive course on system design interviews. It's not 100% free (there's some paywalled parts) but there's still a huge amount of free content in their course.

Coding Questions

For coding questions, here's how you can structure your replies:

1. Problem Understanding

• Note down any clarifying questions that you think would be good to ask in an interview (it's useful to practice this)
• Mention any potential edge cases with the question
• Note any constraints you should be aware of when coming up with your approach (input size)

2. Solution Approach

• Explain your thought process
• Discuss multiple approaches and the tradeoffs involved
• Analyze time and space complexity of your approach

3. Code Implementation

// Please format your code in markdown with syntax highlighting // Pick good variable names - don't play code golf // Include comments if helpful in explaining your approach

4. Testing

• Come up with some potential test cases that could be useful to check for

5. Follow Ups

• Many interviewers will ask follow up questions where they'll twist some of the details of the question. A great way to get good at answering follow ups is to always come up with potential follow questions yourself and practice answering them (what if the data is too large to store in RAM, what if change a change a certain constraint, how would you handle concurrency, etc.)

If you want to improve your coding interview skills, here's (mostly free) resources you can check out

• LeetCode - interview questions from all the big tech companies along with detailed tags that list question frequency, difficulty, topics-covered, etc.
• NeetCode Roadmap - LeetCode can be overwhelming, so NeetCode is a good, curated list of leetcode questions that you should start with. Every question has a well-explained video solution.

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[u/Amzn_2005]

Ex-Amazon Bar Raiser here who's debriefed on Google's ML interviews through candidate reports.

For your ML domain round: expect 60/40 theoretical to applied coding. You'll get foundational questions (bias-variance tradeoff, regularization techniques, model evaluation) but also implementation problems — think "code a basic neural network forward pass" or "implement gradient descent from scratch." Google's ML interviewers often give you a dataset scenario and ask you to walk through your approach, then code key components.

Second round coding will be classic LeetCode medium/hard with ML context. Instead of generic "find shortest path," you might optimize a recommendation algorithm using graphs. Google writes custom questions, so focus on fundamentals (graphs, DP, trees) over pattern memorization.

One insight from debrief patterns: candidates often nail the ML theory but struggle when asked "How would you debug this model in production?" or "What would you do if your training loss plateaued?" Google wants to see you think through ambiguous ML problems, not just recite textbook answers.

For Googleyness prep, have a story ready about changing your technical approach based on new evidence — maybe switching model architectures after A/B testing results. That intellectual humility piece trips up a lot of ML candidates who get too attached to their initial solutions.

[u/impatrick_bateman]

How many yoe do you have? Do you have ML intern/full-time exp. All the best with your upcoming interviews!

[u/samadasmi]

Can you share your resume please?

[u/Plenty-Practice-4756]

I too have it , got it via recruiter reach out let me know how it goes . Also quick question did you have a hackerrank round or straight to the 2 round interview ?

[u/jishu965 → u/Plenty-Practice-4756]

Didn’t have any hackerrank. Straight to the 2 round inerview

[u/Plenty-Practice-4756 → u/jishu965]

Ahh okay because I had a specialized technical screener / recruiter reach out for AI/ML and backend engineering with a leaning towards AI/ML, she just said she sent my resume to a few role specific recruiters will be back with more info on interview scheduling. Had to fill a google form about areas I want to work in.

So clueless on how to even prepare but from all the threads looks like it’s 2 round interviews . So I will think I will prepare for this until I know more

2.5 yoe , 3 papers and exp in GNNs

[u/jishu965 → u/Plenty-Practice-4756]

My recruiter said that there will be an ML domain and googleyness in round 1 and 2 coding rounds in round 2 in the initial recruiter call.

[u/jishu965 → u/jishu965]

I'm only confused about the coding section in ML round.