Machine Learning Engineer Interview Questions

Machine Learning Engineer Interview Questions

Les entreprises s’appuient sur les machine learning engineers pour les aider à concevoir et à améliorer les systèmes qui permettent à leurs logiciels de s’améliorer eux-mêmes, plutôt que d’être programmés. Au cours de l’entretien, préparez-vous à être longuement interrogé sur vos connaissances en informatique et en science des données et, en particulier, sur votre capacité à reconnaître des modèles et des tendances. Un diplôme en informatique ou dans un domaine équivalent sera exigé.

Questions d'entretien d'embauche fréquentes pour un machine learning engineer (H/F) et comment y répondre

Question 1

Question 1 : Quels sont les algorithmes, termes de programmation et théories les plus importants à maîtriser en tant que machine learning engineer ?

How to answer
Comment répondre : Préparez-vous à parler de sujets tels que les erreurs de type I et de type II, l’apprentissage automatique supervisé et non supervisé, les courbes ROC et d’autres éléments clés de l’apprentissage automatique. Les employeurs veulent s’assurer que vous avez une solide connaissance des aspects techniques du poste à pourvoir.
Question 2

Question 2 : Comment expliquer l’apprentissage automatique à quelqu’un qui ne comprend pas ce domaine ?

How to answer
Comment répondre : Parfois, les machine learning engineers doivent travailler avec des personnes qui ne sont pas familières avec les aspects techniques du travail. Saisissez l’occasion que vous offre cette question pour montrer votre solide connaissance du poste et vos capacités de communication.
Question 3

Question 3 : Comment se tenir informé des dernières nouveautés et tendances en matière d’apprentissage automatique ?

How to answer
Comment répondre : En expliquant comment vous vous tenez au courant des dernières nouveautés et tendances en matière d’apprentissage automatique, vous pouvez montrer à un employeur que vous êtes engagé dans le secteur, que vous êtes un chercheur compétent et que vous êtes motivé.

8,195 machine learning engineer interview questions shared by candidates

Algorithms and Data Structure. Typical Leetcode/Hackerrank questions. You will use an online coding tool to do the actual coding and explain your thoughts. 1. Balanced Brackets, determine a string of brackets has a balanced structure,.
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Machine Learning Engineer

Interviewed at Qualcomm

3.8
Jan 30, 2018

Algorithms and Data Structure. Typical Leetcode/Hackerrank questions. You will use an online coding tool to do the actual coding and explain your thoughts. 1. Balanced Brackets, determine a string of brackets has a balanced structure,.

1. Reverse a Linked List (Python) Question: Describe how you would reverse a linked list in Python. Details: The interviewer asked for a function that takes the head of a linked list and reverses it, returning the new head of the reversed list. They were interested in understanding the logic and efficiency of your approach. 2. Remove Cycles from a Graph Question: How would you remove cycles from a graph given an integer n representing node IDs and a list of tuples representing edges? Details: The task was to provide an algorithm that removes cycles from a graph and outputs a list of edges of the new graph with cycles removed. The interviewer was looking for knowledge of graph theory and algorithms to detect and remove cycles. 3. Calculate Calories Burned During a Ride (Python) Question: Write a Python function to calculate the calories burned during a ride based on the rider's weight and ride data. Details: The function needed to calculate the total calories burned given the weight of the rider and a list of tuples representing different segments of the ride, each with a duration and speed. 4. Find the Maximum Sum of Two Numbers in a List (Python) Question: Write a Python function to find the maximum sum of any two numbers in a list. Details: The interviewer wanted to see how you would identify the two largest numbers in a list and sum them up efficiently, demonstrating your problem-solving skills with basic list operations. 5. Merge Two Sorted Lists (Python) Question: How would you merge two sorted lists into one sorted list in Python? Details: The task was to create a function that merges two pre-sorted lists into a single sorted list, showing your understanding of list operations and efficiency in merging algorithms.
May 21, 2024

1. Reverse a Linked List (Python) Question: Describe how you would reverse a linked list in Python. Details: The interviewer asked for a function that takes the head of a linked list and reverses it, returning the new head of the reversed list. They were interested in understanding the logic and efficiency of your approach. 2. Remove Cycles from a Graph Question: How would you remove cycles from a graph given an integer n representing node IDs and a list of tuples representing edges? Details: The task was to provide an algorithm that removes cycles from a graph and outputs a list of edges of the new graph with cycles removed. The interviewer was looking for knowledge of graph theory and algorithms to detect and remove cycles. 3. Calculate Calories Burned During a Ride (Python) Question: Write a Python function to calculate the calories burned during a ride based on the rider's weight and ride data. Details: The function needed to calculate the total calories burned given the weight of the rider and a list of tuples representing different segments of the ride, each with a duration and speed. 4. Find the Maximum Sum of Two Numbers in a List (Python) Question: Write a Python function to find the maximum sum of any two numbers in a list. Details: The interviewer wanted to see how you would identify the two largest numbers in a list and sum them up efficiently, demonstrating your problem-solving skills with basic list operations. 5. Merge Two Sorted Lists (Python) Question: How would you merge two sorted lists into one sorted list in Python? Details: The task was to create a function that merges two pre-sorted lists into a single sorted list, showing your understanding of list operations and efficiency in merging algorithms.

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