Candidatei-me online. O processo levou 3 semanas. Fui entrevistado pela SpaceX (Seattle, WA) em mai. de 2016
Entrevista
The full interview process has four stages: first a debugging quiz, then a phone screen, then a programming project, then an on-site interview.
The debugging quiz is looking for simple off by one errors, memory leaks, etc. They don't give you anything insanely complicated, just some 10-15 line functions. The phone screen is pretty typical, based on my experience they don't ask you for anything beyond what someone qualified for the job should know.
I got to the programming project which I can't say too much about because they make you sign an NDA. It was a 6 hour project which didn't involve any specialized knowledge, anyone with a programming degree or equivalent experience should be able to implement it. Whether or not you can implement in time however is another question, and unfortunately due to poor time management on my part I was not able to complete it.
Perguntas de entrevista [1]
Pergunta 1
What is the difference between a reference and a pointer?
Recruiting Call -> Several rounds of technical interview: very fundamental questions that probe your conceptual understanding. Make sure to study / review first principles as it gets theorectical. Quick 30 minute phone calls
Perguntas de entrevista [1]
Pergunta 1
Tell me about one project to showcase engineering skills
Fiz uma entrevista na empresa SpaceX (California City, CA).
Entrevista
I applied for Software Engineer Data position. It was fine. 1 hour leetcode style interview on codility. The difficulty was medium. I had an alright experience. Was able to get brute force but not optimized solution.
Fiz uma entrevista na empresa SpaceX (Hawthorne, CA).
Entrevista
Recruiter screen was a lot of trivia, very basic trivia that any software engineer should know so make sure to read up on some python syntax etc. to be able to answer the trivia questions. can be tricky given time limit
Perguntas de entrevista [1]
Pergunta 1
What are some basic python methods used in machine learning