Interview Questions

Tian H. - "to add! health assistant! remind me to do physical check, aggregate my health info including sleep, physic check results. ...."See full answer

Ekta M. - "I would start with some clarifying questions like: Is there a deadline when all these needs to be updated by? Do we have upgrade scripts ready? When do we have change freeze? Once I have these few clarifying answers I would start planning: I would meet with all the teams involved in the upgrades Document any resources downtime during the upgrade create a risk registry along with mitigation plan Roll back plan create a phased rollout plan based on deadline Post upgrade get a"See full answer

Chethan N. - "Build a counter using queue, one queue per service ("a", "b") and one with just timestamps to get the overall load. Build rate limiter service using the counter and interviewer asked if there rate limiter might use a different instance of a counter"See full answer

Anonymous Stork - "For Xbox, the next-generation product I propose is a virtual reality headset. The rationale is threefold: Industry Trends: Competitors like Meta and Apple are investing heavily in VR/AR, signaling strong market potential. Xbox Legacy: Xbox has a history of pushing innovation in gaming hardware (e.g., Kinect), and VR represents the next frontier beyond traditional consoles. Strategic Need: With console sales flattening, Xbox must expand into new experiences that deepen engagement and different"See full answer

Frederick K. - "\# An program that prints out the peak elements in a list of integers. Pseudocode: 1. Define a function that takes a list of integers as input. 2. Initialize an empty list to store the peak elements. 3. Loop through the list of integers. 4. For each element, check if it is greater than its neighbors. 5. If it is, add it to the list of peak elements. 6. Return the list of peak elements. def findpeakelements(nums): if not nums: return [] peaks = [] n = len(nums"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

Anchal V. - "understand the top priorities and rank each feature based on value and effort criteria. Scope: emphasize on clarity and risk assessment of the features. In tough deadlines what is must within the feature. highlight the tradeoff early based on the above two"See full answer

Anjali M. - "Why is META AI important? Should company invest in it? What would be the goals and metrics for META AI. Meta AI -native AI infra layer embedded across FoApps( Insta, whatsapp, messenger, Ads) etc. AI is changing user behavior across different verticals, and is shaping how users will create or consume content in the near future. Leading players in this space: Google, OpenAI, and Claude. Not having Meta’s own AI would mean relying on these players to leverage AI capabilities. They get access to"See full answer