Product Manager · Senior-Level (7 YOE)
Location: San Francisco Bay AreaReport date: Feb 13, 2026Equity included
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The first question involved optimizing task completion given time constraints. I received two lists: one representing the time required for each task, and another representing the time already spent on each task. Given a total time 'x', I needed to prioritize...
In the first round, I was asked about the following: * Transformer structure * Advantages of Transformers compared to other models * Differences between Adam and AdamW * PPO concepts * VQVQE training challenges * RoPE formula * Differences between CLIP and Qwe...
The coding questions I encountered were: 1. **Virtual Machine Allocation:** There are *n* types of virtual machines with given initial inventory counts. *m* customers request to rent machines. Each customer rents from the type with the highest current inventor...
## Preparation Tips & Key Takeaways ### What I Learned - I need to brush up on fundamental machine learning concepts, including gradient descent, loss functions, and backpropagation. - I should be prepared to discuss the mathematical formulas behind these conc...
The first problem involved a string containing 0, 1, and ! characters. A ! appears when a '10' or '01' subsequence pair is present in the string. Given an error string like '101!1', I needed to calculate the total number of errors. The approach involved replac...
The online assessment had two questions. **Question 1 (40 minutes):** I was asked to construct a lexicographically largest string 's' of length 'm'. In 'm' operations: * Choose any available element from a value list and append it to 's' (available if state\[i...
The interviewer focused on my past experiences. I spent time explaining the specific protocol I had worked on, detailing the methods I used to solve a challenging NLP problem, and discussing the challenges I faced while collaborating with other annotators.