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Machine Learning Engineer Interview Questions

Review this list of 292 Machine Learning Engineer interview questions and answers verified by hiring managers and candidates.
  • OpenAI logoAsked at OpenAI 
    Add answer
    Video answer for 'How do you select input for modeling if there are features highly correlated with each other?'
    Machine Learning Engineer
    Concept
    +2 more
  • Amazon logoAsked at Amazon 
    4 answers
    +1

    "in simple words, linear regression helps in predicting the value whereas logistics regression helps in predicting the binary classification. But lets talk through some example Linear regression model: E-commerce website pricing recommendation engine is built on linear regression model where we do have some variables such as competitor price, internal economics and consumer demand etc when we put this in a supervised learning model, it helps in predicting prices Logistics regression model"

    Anonymous Aardvark - "in simple words, linear regression helps in predicting the value whereas logistics regression helps in predicting the binary classification. But lets talk through some example Linear regression model: E-commerce website pricing recommendation engine is built on linear regression model where we do have some variables such as competitor price, internal economics and consumer demand etc when we put this in a supervised learning model, it helps in predicting prices Logistics regression model"See full answer

    Machine Learning Engineer
    Concept
    +1 more
  • Amazon logoAsked at Amazon 
    2 answers

    "In 2019, I was given a very important problem to solve. In a team of 3 we had to build a mobility assist device. The customer segment we would go for was something we could decide. The project was very close to me as I had lost someone I loved because of cancer and I saw how reduced mobility was a huge pain point in not being able to do physical activities. My team could only think of elderly people as the main target market. As the Head of Product what I did was: 1) I helped them dive even d"

    Soumya S. - "In 2019, I was given a very important problem to solve. In a team of 3 we had to build a mobility assist device. The customer segment we would go for was something we could decide. The project was very close to me as I had lost someone I loved because of cancer and I saw how reduced mobility was a huge pain point in not being able to do physical activities. My team could only think of elderly people as the main target market. As the Head of Product what I did was: 1) I helped them dive even d"See full answer

    Machine Learning Engineer
    Behavioral
    +3 more
  • Amazon logoAsked at Amazon 
    2 answers
    Video answer for 'Implement k-means clustering.'

    "at first I want to know number of cluster I will put random number if I don't know and I will use method called Elbow method or Silhouette Score ,Gap Statistic and Davies–Bouldin Index to know the best number of cluster and I will use scikit-learn library to import kmeans from sklearn.cluster import KMeans kmeans = KMeans(nclusters=2, randomstate=0) kmeans.fit(X) and X this my data "

    Taheia S. - "at first I want to know number of cluster I will put random number if I don't know and I will use method called Elbow method or Silhouette Score ,Gap Statistic and Davies–Bouldin Index to know the best number of cluster and I will use scikit-learn library to import kmeans from sklearn.cluster import KMeans kmeans = KMeans(nclusters=2, randomstate=0) kmeans.fit(X) and X this my data "See full answer

    Machine Learning Engineer
    Analytical
    +5 more
  • Adobe logoAsked at Adobe 
    34 answers
    +30

    "In python def find_duplicates(arr1: List[int], arr2: List[int]) -> List[int]: result = list(set(arr1) & set(arr2)) return result "

    Sammy R. - "In python def find_duplicates(arr1: List[int], arr2: List[int]) -> List[int]: result = list(set(arr1) & set(arr2)) return result "See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +2 more
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  • Amazon logoAsked at Amazon 
    8 answers
    +5

    "A few months ago I joined a micro-services platform engineering team as their manager, at that time my team was struggling to deliver towards an upcoming production deadline for a customer facing product. Production date had been moved 5 times already and there were about 40% of product features which were remaining to be tested and signed off to move to production . I was made responsible to deliver the release of this product within the deadline and turnaround the software delivery throughput."

    Shuchi A. - "A few months ago I joined a micro-services platform engineering team as their manager, at that time my team was struggling to deliver towards an upcoming production deadline for a customer facing product. Production date had been moved 5 times already and there were about 40% of product features which were remaining to be tested and signed off to move to production . I was made responsible to deliver the release of this product within the deadline and turnaround the software delivery throughput."See full answer

    Machine Learning Engineer
    Behavioral
    +2 more
  • Amazon logoAsked at Amazon 
    13 answers
    +10

    " class Node { constructor(data) { this.data = data; this.left = null; this.right = null; } } function diameterOfTree(root) { if (root === null || root.left === null & root.right === null) { return 0; } function countBranch(node, count) { if (node.left === null && node.right === null) { return count; } let left = node.left === null ? 0 : countBranch(node.left, count+1); let right = no"

    Jeff S. - " class Node { constructor(data) { this.data = data; this.left = null; this.right = null; } } function diameterOfTree(root) { if (root === null || root.left === null & root.right === null) { return 0; } function countBranch(node, count) { if (node.left === null && node.right === null) { return count; } let left = node.left === null ? 0 : countBranch(node.left, count+1); let right = no"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +2 more
  • Goldman Sachs logoAsked at Goldman Sachs 
    4 answers
    Video answer for 'Explain Bayes' theorem.'
    +1

    "Is it bad to get the answer a different way? Will they mark that as not knowing Bayes Theorem or just correct as it is an easier way to get the answer? The way I went is to look at what happens when the factory makes 100 light bulbs. Machine A makes 60 of which 3 are faulty, Machine B makes 40 of which 1.2 are faulty. Therefore the pool of faulty lightbulbs is 3/4.2 = 5/7 from machine A and 1.2/4.2 = 3/7 from Machine B."

    Will I. - "Is it bad to get the answer a different way? Will they mark that as not knowing Bayes Theorem or just correct as it is an easier way to get the answer? The way I went is to look at what happens when the factory makes 100 light bulbs. Machine A makes 60 of which 3 are faulty, Machine B makes 40 of which 1.2 are faulty. Therefore the pool of faulty lightbulbs is 3/4.2 = 5/7 from machine A and 1.2/4.2 = 3/7 from Machine B."See full answer

    Machine Learning Engineer
    Concept
    +2 more
  • Meta logoAsked at Meta 
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    Machine Learning Engineer
    System Design
  • Anthropic logoAsked at Anthropic 
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    Machine Learning Engineer
    Behavioral
    +1 more
  • Amazon logoAsked at Amazon 
    14 answers
    Video answer for 'Implement a k-nearest neighbors algorithm.'
    +10

    "Even more faster and vectorized version, using np.linalg.norm - to avoid loop and np.argpartition to select lowest k. We dont need to sort whole array - we need to be sure that first k elements are lower than the rest. import numpy as np def knn(Xtrain, ytrain, X_new, k): distances = np.linalg.norm(Xtrain - Xnew, axis=1) k_indices = np.argpartition(distances, k)[:k] # O(N) selection instead of O(N log N) sort return int(np.sum(ytrain[kindices]) > k / 2.0) `"

    Dinar M. - "Even more faster and vectorized version, using np.linalg.norm - to avoid loop and np.argpartition to select lowest k. We dont need to sort whole array - we need to be sure that first k elements are lower than the rest. import numpy as np def knn(Xtrain, ytrain, X_new, k): distances = np.linalg.norm(Xtrain - Xnew, axis=1) k_indices = np.argpartition(distances, k)[:k] # O(N) selection instead of O(N log N) sort return int(np.sum(ytrain[kindices]) > k / 2.0) `"See full answer

    Machine Learning Engineer
    Coding
    +2 more
  • Visa logoAsked at Visa 
    1 answer

    "There are couple of reasons for it - Kind of role : Its a product manager role loaded with analytical work, So working with data in stringent regulatory guideline make it more exciting and thrilling. Location & industry is like - Cherry on the cake, Bangalore weather and BFI is at its all time peak as people spending behavior is changing continuously, it will be interesting to see big giants like visa are managing it."

    Nidhi S. - "There are couple of reasons for it - Kind of role : Its a product manager role loaded with analytical work, So working with data in stringent regulatory guideline make it more exciting and thrilling. Location & industry is like - Cherry on the cake, Bangalore weather and BFI is at its all time peak as people spending behavior is changing continuously, it will be interesting to see big giants like visa are managing it."See full answer

    Machine Learning Engineer
    Behavioral
    +4 more
  • TikTok logoAsked at TikTok 
    Add answer
    Machine Learning Engineer
    Machine Learning
    +1 more
  • Google logoAsked at Google 
    4 answers
    +1

    "You can ask some clarifying questions like 1) Ask if the list is already sorted or not 2) is zero included in the list ? 3) Natural numbers are usually positive numbers ( clarify they are non negatives) Solution : 1) If sorted use two pointers and sort them in O(N) 2) if not sorted , -ve / only +ve numbers in the list doesn't matter - the easiest solution is Use a priority queue and push the number and its square in each iteration Finally return the list returned by the priority Queue. N"

    Bless M. - "You can ask some clarifying questions like 1) Ask if the list is already sorted or not 2) is zero included in the list ? 3) Natural numbers are usually positive numbers ( clarify they are non negatives) Solution : 1) If sorted use two pointers and sort them in O(N) 2) if not sorted , -ve / only +ve numbers in the list doesn't matter - the easiest solution is Use a priority queue and push the number and its square in each iteration Finally return the list returned by the priority Queue. N"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +1 more
  • Anthropic logoAsked at Anthropic 
    Add answer
    Machine Learning Engineer
    Artificial Intelligence
    +3 more
  • Meta logoAsked at Meta 
    1 answer

    "I once had to change a decision i had previously made when I got stakeholder feedback that seemed to contradict what was already designed or already even built - such as the way a page was architected or the designs or colors used on a page. I had a justification for all decisions made, but sometimes the stakeholder feedback brings a perspective, such as a part of the user experience, that I had not thought of before. So I then went back to the original design or product and made an adjustment o"

    Sarah K. - "I once had to change a decision i had previously made when I got stakeholder feedback that seemed to contradict what was already designed or already even built - such as the way a page was architected or the designs or colors used on a page. I had a justification for all decisions made, but sometimes the stakeholder feedback brings a perspective, such as a part of the user experience, that I had not thought of before. So I then went back to the original design or product and made an adjustment o"See full answer

    Machine Learning Engineer
    Behavioral
    +1 more
  • Adobe logoAsked at Adobe 
    53 answers
    +49

    "Arrays.sort(inputarray) sliding window with a size of 2. Check for the sum in the sliding window. subtract the start when window moves"

    Sridhar R. - "Arrays.sort(inputarray) sliding window with a size of 2. Check for the sum in the sliding window. subtract the start when window moves"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +5 more
  • Amazon logoAsked at Amazon 
    10 answers
    Video answer for 'What is your leadership style?'
    +7

    "My leadership style is flexible and adaptive, it varies depending on the team members and the needs of the company. My leadership goal is to empower the team and inspire and grow leaders. In order to achieve that, I combine transformational, democratic and coaching leadership styles. Usually when we are facing a new type of challenge, or at the early stage of a project, I like to adapt the transformational leadership which allows me to listen to all the suggestions from the team members and sta"

    onering2ruleall - "My leadership style is flexible and adaptive, it varies depending on the team members and the needs of the company. My leadership goal is to empower the team and inspire and grow leaders. In order to achieve that, I combine transformational, democratic and coaching leadership styles. Usually when we are facing a new type of challenge, or at the early stage of a project, I like to adapt the transformational leadership which allows me to listen to all the suggestions from the team members and sta"See full answer

    Machine Learning Engineer
    Behavioral
    +5 more
  • Machine Learning Engineer
    Machine Learning
  • Meta logoAsked at Meta 
    1 answer

    "FN Given text need to figure out is it following guidelines. Should notify the user in case of not following guidelines. Reason for failure should have misleading/spam/adult filters. NFN High availability High Scalability Low latency of processing Estimations 1M requests/min text - 10kb => 9.5GB/min => 14TB/day API fetchmoderationscore(text) score will be between 0 to 1 more than 0.8 => not following guidelines fetchmoderationscore(text, filter)"

    Deepak K. - "FN Given text need to figure out is it following guidelines. Should notify the user in case of not following guidelines. Reason for failure should have misleading/spam/adult filters. NFN High availability High Scalability Low latency of processing Estimations 1M requests/min text - 10kb => 9.5GB/min => 14TB/day API fetchmoderationscore(text) score will be between 0 to 1 more than 0.8 => not following guidelines fetchmoderationscore(text, filter)"See full answer

    Machine Learning Engineer
    System Design
Showing 81-100 of 292