Member Technical Staff Interview Questions

17,591 member technical staff interview questions shared by candidates

How do you reverse print a string. After answering the same by providing an out of the box API, the next unexpected question was "What if it does NOT exist". While and 2nd alternative was provided, it was pretty much shot down as being not acceptable.
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Senior Member of Technical Staff

Interviewed at VMware

4.4
Aug 2, 2012

How do you reverse print a string. After answering the same by providing an out of the box API, the next unexpected question was "What if it does NOT exist". While and 2nd alternative was provided, it was pretty much shot down as being not acceptable.

Gaussian linear models are often insufficient in practical applications, where noise can be heavy- tailed. In this problem, we consider a linear model of the form yi = a · xi + b + ei. The (ei) are independent noise from a distribution that depends on x as well as on global parameters; however, the noise distribution has conditional mean zero given x. The goal is to derive a good estimator for the parameters a and b based on a sample of observed (x, y) pairs. 1.1 Instructions: 1. Load the data, which is provided as (x, y) pairs in CSV format. Each file contains a data set generated with different values of a and b. The noise distribution, conditional on x, is the same for all data sets. 2. Formulate a model for the data-generating process. 3. Based on your model, formulate a loss function for all parameters: a, b, and any additional parameters needed for your model. 4. Solve a suitable optimization problem, corresponding to your chosen loss function, to obtain point estimates for the model parameters. 5. Formulate and carry out an assessment of the quality of your parameter estimates. 6. Try additional models if necessary, repeating steps 2 − 5.
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Member of the Research Staff

Interviewed at Voleon

4.5
Apr 28, 2017

Gaussian linear models are often insufficient in practical applications, where noise can be heavy- tailed. In this problem, we consider a linear model of the form yi = a · xi + b + ei. The (ei) are independent noise from a distribution that depends on x as well as on global parameters; however, the noise distribution has conditional mean zero given x. The goal is to derive a good estimator for the parameters a and b based on a sample of observed (x, y) pairs. 1.1 Instructions: 1. Load the data, which is provided as (x, y) pairs in CSV format. Each file contains a data set generated with different values of a and b. The noise distribution, conditional on x, is the same for all data sets. 2. Formulate a model for the data-generating process. 3. Based on your model, formulate a loss function for all parameters: a, b, and any additional parameters needed for your model. 4. Solve a suitable optimization problem, corresponding to your chosen loss function, to obtain point estimates for the model parameters. 5. Formulate and carry out an assessment of the quality of your parameter estimates. 6. Try additional models if necessary, repeating steps 2 − 5.

There is a dependency management system like maven, different class dependencies are given, print an order in which they are to be loaded, also identify a case when such an algorithm will fail: Input: A -> B, C B-> C C - > D D - >E E F - > A Output: E D C B A F
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Member of Technical Staff

Interviewed at Nutanix

3.8
Feb 4, 2020

There is a dependency management system like maven, different class dependencies are given, print an order in which they are to be loaded, also identify a case when such an algorithm will fail: Input: A -> B, C B-> C C - > D D - >E E F - > A Output: E D C B A F

Architecture of my previous projects. Mostly LC Easy/Medium (Interval problems, Graphs and Trees, can't be more specific due to NDA). Challenging behavioral questions. Understanding of design, tests and code review. Questions on REST Api design patterns, basic security concepts.
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Senior Member of Technical Staff

Interviewed at Salesforce

4.1
Feb 25, 2020

Architecture of my previous projects. Mostly LC Easy/Medium (Interval problems, Graphs and Trees, can't be more specific due to NDA). Challenging behavioral questions. Understanding of design, tests and code review. Questions on REST Api design patterns, basic security concepts.

questions were mostly based on computer networks, operating systems and dbms. No questions at all on programming or data structures. Only theoretical knowledge is not sufficient, questions were mostly application oriented.
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Member of Technical Staff [QA]

Interviewed at Commvault

3.8
Aug 11, 2016

questions were mostly based on computer networks, operating systems and dbms. No questions at all on programming or data structures. Only theoretical knowledge is not sufficient, questions were mostly application oriented.

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