Machine Learning Engineer Technical Interview Questions

Anonymous Partridge - "We will have to use a second more powerful LLM Model to validate the answers. LLM as a judge"See full answer

Alex N. - "The adjusting context window size in LLM change trade off between reasoning capability, accuracy, computation cost. It influence how attention mechanist allocate resources across the input. Longer context window let it you input greater number of words and have more context to generate proper next token. However llms have lost in the middle issue. They remember the beginning of text and end of text but lost information located in the middle of long input. Another problem is Attention Dilution."See full answer

Srini K. - "performance issues and sudden spikes on input requests by scaling techniques and optimization."See full answer

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

Surbhi G. - "Deep Learning is a part of Artificial Intelligence, it's like teaching the machine to think and make decisions on its own. It's like how we teach a child the concept of an apple - it's round, red, has a stem on top. We show them multiple pictures of apples and then they understand and can recognize an apple in future. Similarly, we feed lots of data to the machine, and slowly, it starts learning from that data, and can then make relevant predictions or decisions based on what it has learnt. A co"See full answer

Darpan D. - "Clarifying When we say cloud gaming, we refer to a video gaming experience using cloud computing, right? Assumption: Yes. Understanding of cloud computing first. I'll use some analogies: Imagine you are looking to do heavy computing but don't have a powerful CPU and GPU. CPU and GPU are like your big calculators. You can buy a powerful CPU and GPU, but problems: It costs a lot to buy. It costs a lot to run. You don't need it 24-7. You are not a un"See full answer

Anmol R. - "The example given is wrong. The 2nd test case should have answer 3, as we can get to 6 by using 3 coins of denomination 2."See full answer

Madhur K. - "I have worked with ML when I was a PM for Customer Due Diligence and it required recalibration to improve the matching logic (for screening and Proof of business matching with Google) and threshold analysis. In this scenario we had to extract past True positive, False positive decisions from operations and run threshold analysis to come up with a new threshold to match better and remove the noise i.e. False positives. Taking this new threshold for matching, the ML algorithm is receiving feedback"See full answer

Ravi K. - "voice"See full answer