Google DeepMind Machine Learning Engineer Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 5 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Google DeepMind.
Google DeepMind
Machine Learning Engineer
Mid Difficult Positive experience No offer 5 rounds
Interview process
Recruiter call Phone screen Technical screen Onsite
Interview formats
Technical Behavioral Coding System Design
So, for the Google DeepMind Machine Learning Engineer role, it's usually like a three-part thing. First up, there's a phone screening where they'll chat about your tech background, stuff you've done before, and your ML chops. Then, you get into some deeper dives, like technical rounds where they'll grill you on ML concepts, algorithms, coding, and maybe some specific stuff like computer vision or NLP if that's your jam. They also do behavioral interviews to see how you play with others and solve problems. The last bit is the onsite, which has a bunch of rounds – think data structures and algorithms, ML system design, and then some leadership or HR chats, sometimes even with a VP. Basically, you gotta show you're technically solid, can figure things out, and fit in with Google's vibe, you know, 'Googleyness'.
Confirmed questions8 questions
- Can you walk me through a machine learning project you were involved in, highlighting the obstacles encountered, the technologies utilized, and the metrics for success?
- Tell me about your technical background, previous projects, and your expertise in machine learning.
- How would you approach questions about machine learning concepts, algorithms, and coding proficiency?
Google DeepMind
Machine Learning Engineer
Intern Average Positive experience No offer 1 round
Interview process
Technical screen
Interview formats
Coding Technical
It was an internship. I was asked for Leetcode medium and hards, like "best time to sell stock" and DFS algos. The interviewers were really polite and supportive. I couldn't answer the graph algorithm question.
Confirmed questions2 questions
- Can you solve the 'best time to sell stock' problem?
- Can you implement DFS graph algorithms?
Google DeepMind
Machine Learning Engineer
Mid Difficult Negative experience No offer 3 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Behavioral Technical Presentation
First interview to get to know each other, with the CEO of DeepMind. Presented my academic and professional background, presented DeepMind, and described the job. Then, a technical test with a senior employee, followed by a meeting with the DeepMind team.
Confirmed questions2 questions
- Could you explain the Expectation-Maximization algorithm?
- What about the architecture of an RNN?
Google DeepMind Machine Learning Engineer Interview Questions
Quoted word for word from Google DeepMind interview reports.
“What about the architecture of an RNN?”
Read reports →“Could you explain the fundamentals of Support Vector Machines?”
Read reports →“Could you explain the Expectation-Maximization algorithm?”
Read reports →“Can you implement DFS graph algorithms?”
Read reports →“Can you solve the 'best time to sell stock' problem?”
Read report →“How do you embody 'Googleyness' and fit into Google's culture and values?”
Read report →“Describe your approach to designing machine learning systems.”
Read report →“Can you talk about a recent deep learning method you've applied?”
Read report →“Can you explain your understanding of data structures and algorithms?”
Read report →Formats, difficulty and experience
Across all 5 Google DeepMind interview reports.