Perplexity Software Engineer Phone Screen Questions

It's not easy for older programmers to find jobs again; they're waiting for the results. Please send blessings and add rice (a Chinese internet slang term for virtual currency) Position: Staff SWE Rou

Given a string and a list of stop words, return the string up to the first stop word. What if the input string is a stream? The entire string cannot be loaded into memory.

The topic is Embedding Model Server. The following content requires a score higher than 189. You can already view it. Provide an Embedding Model class. You need to implement a service to use this mode

## Problem You have `n` servers and a list of request assignments `(server_id, request_weight)`. A distribution is considered "balanced" if the maximum total weight on any server minus the minimum total weight is at most `threshold`. Write a function that checks whether a given assignment is balanced and, if not, returns the servers causing the imbalance. ```python def check_distribution( n: int, assignments: list[tuple[int, float]], threshold: float ) -> tuple[bool, list[int]]: """Return (is_balanced, list_of_imbalanced_server_ids).""" pass ``` ``` Input: n=3, threshold=5.0 assignments = [(0,10),(1,8),(2,20),(0,5),(1,7)] # Server totals: 0->15, 1->15, 2->20 # max-min = 20-15 = 5 <= 5 -> balanced Output: (True, []) assignments = [(0,10),(1,3),(2,20)] # Totals: 0->10, 1->3, 2->20. max-min=17 > 5 Output: (False, [1, 2]) ``` ## Follow-ups 1. Define "imbalanced server" clearly — is it servers above average, below average, or at both extremes? 2. How would you rebalance by moving the minimum number of requests? 3. Extend to a real-time streaming version where `check_distribution` is called after each new assignment. 4. How would you write a SQL query to find imbalanced servers if assignments are stored in a table?

## Problem Validate a dependency graph for cycles or ordering conflicts, using topological sort. ## Likely LeetCode equivalent Similar to LC 207 Course Schedule. ## Tags coding, graph, topological_sort, phone

## Problem Given a list of text documents and a stopword list, remove all stopword occurrences from each document. Matching is case-insensitive. Preserve original word casing for non-stopwords. Return the filtered documents. ```python def remove_stopwords( documents: list[str], stopwords: list[str] ) -> list[str]: pass ``` ``` Input: documents = ["The quick brown fox", "A dog and a cat"] stopwords = ["the", "a", "and"] Output: ["quick brown fox", "dog cat"] # Extra spaces collapsed, original case preserved for kept words. Input: documents = ["IS THIS WORKING"] stopwords = ["is", "this"] Output: ["WORKING"] ``` ## Follow-ups 1. What data structure do you use for stopword lookup, and why? 2. How do you handle punctuation attached to words (e.g., `"fox,"` where `"fox"` is a stopword)? 3. For a corpus of 10 million documents, how would you parallelize this pipeline? 4. Extend to support language-specific stopword lists that are selected based on detected document language.