Machine Learning Engineer applicants have rated the interview process at Google with 3.3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 62% positive. To compare, the company-average is 61.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 32 days to get hired, when considering 26 user submitted interviews for this role. To compare, the hiring process at Google overall takes an average of 38 days.
Common stages of the interview process at Google as a Machine Learning Engineer according to 26 Glassdoor interviews include:
Phone interview: 32%
Skills test: 24%
One on one interview: 12%
Presentation: 9%
IQ intelligence test: 6%
Background check: 6%
Other: 3%
Drug test: 3%
Personality test: 3%
Group panel interview: 3%
Here are the most commonly searched roles for interview reports -
Hard system design and DSA questions. Coding session were not take home assignments and went deep into technical SWE. Long gruelling session but everyone was nice. Lasted for about 3 hours and hardly answered any correctly
Standard interview. I was contacted by the recruiter and was matched with a team pretty relevant to my job. One phone interview, one fit chat, 4 rounds of onsite interviews.
Interview questions [1]
Question 1
Implement a MHA class, together with some modeling questions related to SOTA models.
pas eu d'entretien. jamais répondu. pourtant j'avais un super cv et une recommendation d'une personne travaillant la bas. donc très déçu de l'administration chez google. je pense que les cv passe par des IA qui prennent que des gens de Stanford
Na entrevista foram feiras perguntas condizentes com o cargo, sem fugir do tema, Estrutura de modelos e experiencias profissionais. Além disso, boas praticas com modelos de IA e ciclo de vida de modelos.