Applied Scientist applicants have rated the interview process at Amazon Web Services with 3.1 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 40% positive. To compare, the company-average is 57.6% positive. This is according to Glassdoor user ratings.
Candidates applying for Applied Scientist roles take an average of 1 day to get hired, when considering 10 user submitted interviews for this role. To compare, the hiring process at Amazon Web Services overall takes an average of 36 days.
Common stages of the interview process at Amazon Web Services as a Applied Scientist according to 10 Glassdoor interviews include:
One on one interview: 30%
Phone interview: 20%
Skills test: 20%
Background check: 10%
Group panel interview: 10%
Presentation: 10%
Here are the most commonly searched roles for interview reports -
I applied through a recruiter. I interviewed at Amazon Web Services (Seattle, WA) in Nov 2024
Interview
Recruiter reached out via LinkedIn. Not very responsive. I didn't know the format of interview by the day of interview. One of the recruiter said it would be with HR and LP based, one said it would be ML death and breadth. Eventually, the interview was about basic ML and NN questions. There was no question from the resume, and leetcode.
Interview questions [1]
Question 1
They asked bias and variance trade off: the math formula for it, activation functions pros and cons specifically about tanh, dropout layers, In the end I was asked a graph problem: number of islands. They spend good amount of time on each question. While preparing think about how can you talk about each topic for 3-4 minutes.
Recruiter screen followed by technical interview. Technical interview was not at all as described by recruiter. I was told to prepare for AI/ML fundamentals but was asked to do a deep dive on LLM infrastructure and training from scratch.
Interview questions [1]
Question 1
Describe the encoder, decoder, and encoder/decoder architectures
Lots of ml questions around current state if the art. Llm architecture and training fine tuning more around statistics and computer science fundamentals and math such as linear algebra and probability also explain experience via leadership principles causal in the beginning then more involved with questions about the role in the end friendly encouraging interaction would recommend
Begins with an introductory meeting with the hiring manager, discuss background and experience. This is followed by a coding interview with algorithmic challenges. Next, many behavioral questions focused on leadership principles. Then, a system design interview to architect scalable and maintainable systems. Additionally, ML concepts, algorithms, and practical applications.