Machine Learning Engineer Interview Questions

Machine Learning Engineer Interview Questions

Unternehmen nehmen die Dienste von Machine Learning Engineers in Anspruch, um Systeme zu entwerfen und zu optimieren, mit denen sich ihre Software selbstständig verbessern kann, statt speziell programmiert werden zu müssen. Stellen Sie sich darauf ein, dass während des Vorstellungsgesprächs Ihr Wissen in den Bereichen Informatik und Data Science abgefragt wird. Dabei wird der Schwerpunkt im Zweifelsfall auf dem Erkennen von Mustern und Trends liegen. Erforderlich ist ein Bachelor-Abschluss in Informatik oder einem verwandten Fachgebiet.

Typische Bewerbungsfragen als Machine Learning Engineer (m/w/d) und wie Sie diese beantworten

Question 1

Frage 1: Welches sind die wichtigsten Algorithmen, Programmierbegriffe und Theorien, die man als Machine Learning Engineer verstanden haben muss?

How to answer
So beantworten Sie die Frage: Seien Sie darauf vorbereitet, über Dinge wie Type-I- und Type-II-Fehler, beaufsichtigtes und unbeaufsichtigtes maschinelles Lernen, ROC-Kurven und andere wichtige Aspekte des maschinellen Lernens zu sprechen. Der Arbeitgeber möchte sich vergewissern, dass Sie über fundierte Kenntnisse der technischen Aspekte der zu besetzenden Stelle verfügen.
Question 2

Frage 2: Wie würden Sie jemandem, der es nicht kennt, das Konzept des maschinellen Lernens erklären?

How to answer
So beantworten Sie die Frage: Manchmal müssen Machine Learning Engineers mit anderen Personen zusammenarbeiten, die mit den technischen Aspekten der Tätigkeit nicht vertraut sind. Nutzen Sie diese Frage im Vorstellungsgespräch als Gelegenheit, Ihre guten Kenntnisse über die Stelle und Ihre Kommunikationskompetenzen unter Beweis zu stellen.
Question 3

Frage 3: Wie bleiben Sie über aktuelle News und Trends im Bereich des maschinellen Lernens auf dem Laufenden?

How to answer
So beantworten Sie die Frage: Sprechen Sie darüber, wie Sie bei aktuellsten News und Trends im Bereich des maschinellen Lernens auf dem neuesten Stand bleiben, und zeigen Sie Ihrem potenziellen Arbeitgeber so, dass Sie sich mit der Branche beschäftigen, als Forscher kompetent sind und eine hohe Motivation mitbringen.

8,208 machine learning engineer interview questions shared by candidates

Phone1: Spent 20-25 min out of 45 min talking about what I work right now since they were doing very similar. Then coding - something related to interval problem. Phone2: Same thing spent 25 min out 45 min talking about what I work right now and then 2 sum problem! So my impression was I'm interviewing for Machine Learning role. In between phone/onsite recruiter changed. 1st one told me there will be Machine Learning round for onsite. Second one said we can't tell you much but yeah there will be ML questions. The procedure isn't standardized. She mentioned before interview she will tell me about what all round will be what for onsite. Including giving hint about ML questions. Totally different thing happened at onsite: onsite1: Again interested in what I work on. Asked me what would I like model building vs building ML pipeline. (And THAT according to them is ML question!) And write snake game. easy. onsite2: Design. Autonomous car collects data. We want to get the data out (say speed/location etc) and also push data (like some commands) how would you design. Well broad question but whatever we can do onsite3 (30 min): lunch onsite4: Behavior. I believe this judges your level. As well as you're not jerk! Questions like: Have you faced a situation where your design was wrong etc.. Don't remember onsite5: Ops. WEIRD right? for Machine Learning they asked me Ops!? If you're Amazonian you would nail it. How and where would you put metrics. onsite6(30 min): Car ride. onsite7: Manager round. Something like behavior. After interview: Recruiter: Sorry I couldn't give you details about what all interview will be. But did you find anything odd? Me: Yeah, there were not ML questions. And Ops? I don't know. She: Oh ok, how did you like team ... Me:... Result: Recruiter: Well we're not moving forward cause your ML experience not meeting bar. I was like WTF you didnt ask me any ML question. Me: Could you at least give me feedback? She: 1st round you were asked ML questions and there were not satisfactory. You don't have work experience in ML. ME: well no there were no questions. And yes you're right I've academic experience (I was referred and person had made sure it is fine) She: You were more of generic role but we got just 1 senior eng role open but you're not meeting senior level. Me still: Without asking ML questions how did they decide its no? I believe what they interview for was COMPLETELY different role and senior role - like to let's give it a shot. I'm baffled by their interview process. If you take ML interview and reject me cause I didn't do well on questions - sure makes sense. But why would you reject for something that you haven't interviewed me for?
avatar

May BE Machine Learning Engineer

Interviewed at Uber

3.7
Feb 14, 2018

Phone1: Spent 20-25 min out of 45 min talking about what I work right now since they were doing very similar. Then coding - something related to interval problem. Phone2: Same thing spent 25 min out 45 min talking about what I work right now and then 2 sum problem! So my impression was I'm interviewing for Machine Learning role. In between phone/onsite recruiter changed. 1st one told me there will be Machine Learning round for onsite. Second one said we can't tell you much but yeah there will be ML questions. The procedure isn't standardized. She mentioned before interview she will tell me about what all round will be what for onsite. Including giving hint about ML questions. Totally different thing happened at onsite: onsite1: Again interested in what I work on. Asked me what would I like model building vs building ML pipeline. (And THAT according to them is ML question!) And write snake game. easy. onsite2: Design. Autonomous car collects data. We want to get the data out (say speed/location etc) and also push data (like some commands) how would you design. Well broad question but whatever we can do onsite3 (30 min): lunch onsite4: Behavior. I believe this judges your level. As well as you're not jerk! Questions like: Have you faced a situation where your design was wrong etc.. Don't remember onsite5: Ops. WEIRD right? for Machine Learning they asked me Ops!? If you're Amazonian you would nail it. How and where would you put metrics. onsite6(30 min): Car ride. onsite7: Manager round. Something like behavior. After interview: Recruiter: Sorry I couldn't give you details about what all interview will be. But did you find anything odd? Me: Yeah, there were not ML questions. And Ops? I don't know. She: Oh ok, how did you like team ... Me:... Result: Recruiter: Well we're not moving forward cause your ML experience not meeting bar. I was like WTF you didnt ask me any ML question. Me: Could you at least give me feedback? She: 1st round you were asked ML questions and there were not satisfactory. You don't have work experience in ML. ME: well no there were no questions. And yes you're right I've academic experience (I was referred and person had made sure it is fine) She: You were more of generic role but we got just 1 senior eng role open but you're not meeting senior level. Me still: Without asking ML questions how did they decide its no? I believe what they interview for was COMPLETELY different role and senior role - like to let's give it a shot. I'm baffled by their interview process. If you take ML interview and reject me cause I didn't do well on questions - sure makes sense. But why would you reject for something that you haven't interviewed me for?

Interview questions followed a pretty standard MLE process (mix of coding including ML practical coding, ML system design, behavioral). My recruiter provided a lot of helpful information about what to expect for each round.
avatar

Machine Learning Engineer

Interviewed at Superhuman

3.6
Aug 8, 2024

Interview questions followed a pretty standard MLE process (mix of coding including ML practical coding, ML system design, behavioral). My recruiter provided a lot of helpful information about what to expect for each round.

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