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 interviewed at Amazon Web Services (Bellevue, WA)
Interview
First a screening round followed by 5 round virtual onsite. Screnning consisted of general ML textbook questions on a variety of topics (deep learning, SVM, regression, classification, decision trees). 5VO focused more on role specific questions such as LLMs and Leadership princaples as well as your own prior research background.
Interview questions [1]
Question 1
How do you fit SVM on non linear data?
Describe an acoustic matched filter?
Describe no free lunch theorem?
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.