Amazon Machine Learning Engineer Interview Questions

Anonymous Aardvark - "Recently, I had to make a decision that I could automate a part of a process now and help the operations team reducing 9 hours of manual work to 60 minutes for one client. The second option was to fully automate the end to end process that would take 4 weeks of development, but fully automate the process and that could be rolled out across the board. The process was to change the member's paperless preference to paper when a sent email gets bounced 3 times in a row and inform her with a paper"See full answer

Jane D. - "My approach to dealing with difficult stakeholders has always been: Engage - Directly engage with the stakeholder, meet or chat Listen - Listen to what they have to say, patiently. Understand - Understand their POV, even if it is impossible at some times Ask - Ask clarifying questions. Why? When? What? Engage again - Keep them in the loop until there is closure For example, we were in the final stages of a very important, strategic project for our organization. I was leading th"See full answer

Ushita S. - "A clarifying question: Is this question asking about when I met a tight deadline in a project or how did I manage a project that had a tight deadline? The answer uploaded to this question is good, I would also add 'creating a critical path from overall project schedule and then making sure that none of the deliverables in the critical path are sacrificed in order to meet the tight deadline' as an action taken."See full answer

Aabid S. - "I work at a startup that makes software for Law Enforcement and the FBI. Our product analyzes calls being made by prison inmates and "listens" for predictors of violence and criminal behavior. Our clients are some of the top state prisons in the country. Recently one of the largest states in the country decided to evaluate our product for their prison system. I demo'd the product to the officers and they seemed to like everything. During the presentation they asked us if the product was ADA com"See full answer

Bipin R. - "As you know, this is the most important question for any interview. Here is a structure I like to follow, Start with 'I'm currently a SDE/PM/TPM etc with XYZ company.... ' Mention how you got into PM/TPM/SDE field (explaining your journey) Mention 1 or 2 accomplishments Mention what you do outside work (blogging, volunteer etc) Share why are you looking for a new role Ask the interviewer if they have any questions or will like to dive deep into any of your experience"See full answer

Rajesh V. - "As a PM i received a feedback from my program manager on my style of verbal communication. It is about me speaking faster when i wanted to get away with a topic that i wasn't confident (may be not backed up with data, or still in process of getting detailed insight of a problem etc.). Whereas when I'm confident I tend to speak slowly or more assertively that made people to follow easily. I welcomed that feedback so from then on when I'm not confident in a topic I became more assertive to let pe"See full answer

Dadja Z. - "Traverse the array of points while computing the distance and pushing it to the heap. Then traverse again the heap and pop the k closest. Time O(nlogn) Space O(n)"See full answer

Scott S. - " The Situation A few months ago, our trading platform started experiencing significant latency issues during peak trading hours. This latency was affecting our ability to process real-time market data and execute trades efficiently, potentially leading to substantial financial losses and missed opportunities. Identifying the Problem The first step was to identify the root cause of the latency. I organized a team meeting with our data engineers, DevOps, and network specialists to gather"See full answer

shubh4197 - "I responded by creating a directed graph and applying topological sorting on it"See full answer

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

Avon T. - "Initialize left pointer: Set a left pointer left to 0. Iterate through the array: Iterate through the array from left to right. If the current element is not 0, swap it with the element at the left pointer and increment left. Time complexity: O(n). The loop iterates through the entire array once, making it linear time. Space complexity: O(1). The algorithm operates in-place, modifying the input array directly without using additional data structures. "See full answer

Dinesh K. - "i dont know"See full answer

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

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

Rick E. - " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "See full answer

Komal S. - "a. Sort the array elements. b. take two pointers at index 0 and index Len-1; c. if the sum at the two pointers is target; break and return the pair d. if the sum is smaller, then move left pointer by 1 e. else move right pointer by 1; run the logic till the target is met or right pointer crosses the left pointer."See full answer

TreeOfWisdom - "Should this question be BST, not just BT? Otherwise it would not be possible to reconstruct the tree solely based on the array regardless of its order"See full answer