Machine Learning Engineer Interview Questions

Mark G. - "I look at AI safety, ethics, guardrails, and governance as layers of one core responsibility: making systems useful without letting them cause harm. The Technical Core: Safety Safety is about managing technical risks like reliability, bias, and unintended behavior. It cannot be a final checklist before launch. It has to be part of the whole cycle, from how data is collected to how the system is monitored after it goes live. The Human Element: Ethics Ethics asks if a system should"See full answer

BriskD - "I watched a couple of videos like this, one of them by Exponent staff (I think). It was disappointing that the architecture diagram and the walkthrough was a general layered architecture that you can apply to any backend system. I was wondering if there are videos that can be considered a reference material to watch, learn and improve on the tech (sys design) skills, and not so much about the soft skills."See full answer

Nathan B. - "There are many good answers to this that AI scientists around the world, I and my coworkers have tried over the years. For one, RAG is a great option to fact-check and enforce citation generation, update the data in the knowledge base of the generative AI, etc. "See full answer

Anjali V. - "I feel this is more about "Describe a time when I failed or struggled" rather than "Project Failure"."See full answer

Million D. - "Machine learning software engineer interviews at Google are really challenging. The questions are difficult, specific to Google, and they cover a wide range of topics."See full answer

Kartikeya N. - "C : Okay. So I would want to start with knowing what is the product for which we have to build a recommendation system. I : This is a photo sharing product. C : Okay. So is this something on the lines of Instagram? I : Yes C : Okay. And are we a new product co or we have some current product built already? I : You can assume yourself. C : Okay. Is there any demography or country we are targeting? I : No, this is a global product C : Okay. So, the biggest goal of any product recommendation system"See full answer

Mrinalini R. - "A good answer is describing an experience where you either proposed something that was selected after discussion or an alternate approach was taken, or you disagreed with a decision and argued for something else, either successfully or not. A good answer would be you had cogent arguments, the decision went another way for some reason, and you then fully backed the decision (agree to disagree is another way of stating it). You did not take it personally and you fully committed to the deci"See full answer

Ra R. - "In my time at Snapp! I was in charge of communicating the product backlog to our CEO. We had a shared Jira board that he had access to and I made specifically for him. One day he saw me in the office and said he doesn’t know anything about our backlog and that’s because I failed to communicate with him. I got upset at first because of the fact that I made the dashboard exclusively for him. But I tried to ask questions to understand his point of view in depth. He then mentioned he doesn't have t"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

Kishor J. - "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"See full answer

Zakery K. - "Conflict is a GREAT opportunity to really demonstrate that you care about someone and, through effective conflict resolution, build stronger authentic relationships with the people you work with. When faced with conflict, I prioritize understanding all perspectives involved. I start by actively listening to the other parties: asking clarifying questions to pinpoint the source of the conflict, reflecting back what I'm hearing to make sure I understand them correctly, and ultimately identify"See full answer

Anonymous Prawn - "Would be better to adjust resolution in the video player directly."See full answer

Anchal V. - "supervised learning: model is trained on the labeled data unsupervised learning: no labels provided - model learns by finding patterns , structure and groupings in the data. Semi-supervised learning: use small set of labels to guide learning for the larger pool of unlabeled data. reinforcement learning: leans by interacting with students the environment, receives reward and penalties based on actions self supervised: no labelled data . The model makes its own practice problems by"See full answer

Jacky Y. - "Problem scope: Can this system detect Bot in real-time online or offline? Both. Online traffic: 1M DAU. Latency: 2s. Offline frequency: daily Offline data: 2B activity logs. Data: How do we know a Bot player (Label)? Human label. Imbalance data: reweight, resample. Develop a Bot simulator to generate more data offline for training. Given lower weight to simulator data than human label. Features: Signals from different models online. Log all the features for offline. Propose new features: dail"See full answer

VContaineers - " Compare alternate houses i.e for each house starting from the third, calculate the maximum money that can be stolen up to that house by choosing between: Skipping the current house and taking the maximum money stolen up to the previous house. Robbing the current house and adding its value to the maximum money stolen up to the house two steps back. package main import ( "fmt" ) // rob function calculates the maximum money a robber can steal func maxRob(nums []int) int { ln"See full answer