Machine Learning Engineer applicants have rated the interview process at Accenture with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 68.4% positive. This is according to Glassdoor user ratings.
Candidates applying for Machine Learning Engineer roles take an average of 14 days to get hired, when considering 1 user submitted interviews for this role. To compare, the hiring process at Accenture overall takes an average of 29 days.
Common stages of the interview process at Accenture as a Machine Learning Engineer according to 1 Glassdoor interviews include:
Skills test: 33%
Background check: 33%
Phone interview: 33%
Here are the most commonly searched roles for interview reports -
I applied through college or university. The process took 2 months. I interviewed at Accenture (Bengaluru)
Interview
it was an on-campus opportunity and 1 stage was apti round then the coding round after that there was a communication-based round. The interview was scheduled, and the interviewer was very polite and helping and extremely experienced as a project manager in the company for more than a Decade
Profile Screening checks resume fit. Technical Round covers ML concepts, forecasting, pipelines, MLOps, and coding. Behavioral Round focuses on project discussion, teamwork, communication, challenges, and problem-solving alignment with role expectations.
La entrevista fue bastante básica, enfocada principalmente en conocer mi perfil y entender cómo actuaría en diferentes situaciones laborales. Desde el inicio, pude notar que el objetivo era obtener una visión clara de quién soy profesionalmente, qué tipo de experiencias he tenido y cómo me desenvuelvo en un entorno de trabajo. Las preguntas iban dirigidas a identificar mis fortalezas, mis prioridades y la forma en que suelo organizarme.
Interview questions [1]
Question 1
Las preguntas iban dirigidas a identificar mis fortalezas, mis prioridades y la forma en que suelo organizarme.
Domande su machine learning, algoritmi di clustering, vantaggi e svantaggi, casi in cui usare e casi in cui non ha senso usare determinati modelli
Infine una domanda facile di logica