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Evernorth Health Services Machine Learning Engineer Interview Questions and Answers

Updated 9 Jan 2025

Evernorth Health Services Machine Learning Engineer Interview Experiences

1 interview found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed in Dec 2024. There were 2 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. Types of chunking methods?
  • Q2. How to optimize the RAG Pipeline?
Round 2 - One-on-one 

(2 Questions)

  • Q1. Managerial questions and few dsa questions
  • Q2. Discussion on RAG Pipeline based project

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare for the topics mentioned in your CV and also explore recent advancements in large language models (LLMs).

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
-

I applied via Company Website and was interviewed in Nov 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Logical, Verbal, reasoning 90 mins

Round 2 - Technical 

(2 Questions)

  • Q1. ML algorithms and Explain it?
  • Q2. Print even numbers in for loop?
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Technical 

(3 Questions)

  • Q1. What is evaluation Matrix for classification
  • Ans. 

    Evaluation metrics for classification are used to assess the performance of a classification model.

    • Common evaluation metrics include accuracy, precision, recall, F1 score, and ROC-AUC.

    • Accuracy measures the proportion of correctly classified instances out of the total instances.

    • Precision measures the proportion of true positive predictions out of all positive predictions.

    • Recall measures the proportion of true positive p...

  • Answered by AI
  • Q2. What L1 and L2 regression
  • Ans. 

    L1 and L2 regression are regularization techniques used in machine learning to prevent overfitting.

    • L1 regression adds a penalty equivalent to the absolute value of the magnitude of coefficients.

    • L2 regression adds a penalty equivalent to the square of the magnitude of coefficients.

    • L1 regularization can lead to sparse models, while L2 regularization tends to shrink coefficients towards zero.

    • L1 regularization is also know...

  • Answered by AI
  • Q3. Explain random forest algorithm
  • Ans. 

    Random forest is an ensemble learning algorithm that builds multiple decision trees and combines their predictions.

    • Random forest creates multiple decision trees using bootstrapping and feature randomization.

    • Each tree in the random forest is trained on a subset of the data and features.

    • The final prediction is made by averaging the predictions of all the trees (regression) or taking a majority vote (classification).

  • Answered by AI
Round 2 - HR 

(2 Questions)

  • Q1. Tell me about self
  • Ans. 

    I am a dedicated and passionate Machine Learning Engineer with a strong background in computer science and data analysis.

    • Experienced in developing machine learning models for various applications

    • Proficient in programming languages such as Python, R, and Java

    • Skilled in data preprocessing, feature engineering, and model evaluation

    • Strong understanding of algorithms and statistical concepts

    • Excellent problem-solving and ana

  • Answered by AI
  • Q2. Questions about salary discuss

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Referral and was interviewed in Sep 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Basic Stats questions
  • Q2. Basic ML questions
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected
Round 1 - Technical 

(1 Question)

  • Q1. Started with basic os or network fundamentals like analyzing a core dump, handling tcp packet loss, difference between rest api and grpc etc. Then, from ML started with basic questions like bias variance t...
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Difference between bias and variance
  • Ans. 

    Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.

    • Bias is error introduced by approximating a real-world problem, leading to underfitting.

    • Variance is error introduced by modeling the noise in the training data, leading to overfitting.

    • High bias can cause a model to miss relevant relationships between features and target variable.

    • High variance can cause a model to be overl...

  • Answered by AI
  • Q2. What’s is Learning rate
  • Ans. 

    Learning rate is a hyperparameter that controls how much we are adjusting the weights of our network with respect to the loss gradient.

    • Learning rate determines the size of the steps taken during optimization.

    • A high learning rate can cause the model to converge too quickly and potentially miss the optimal solution.

    • A low learning rate can cause the model to take a long time to converge or get stuck in a local minimum.

    • Com...

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
No response

I applied via Walk-in and was interviewed in Sep 2023. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Coding Test 

Problem solving skills

Round 3 - Aptitude Test 

Logical reasoning numerical reasoning abstract reasoning verbal reasoning

Round 4 - HR 

(3 Questions)

  • Q1. Self introduction
  • Q2. Family background
  • Q3. Salary expectation

Interview Preparation Tips

Topics to prepare for BYJU'S Machine Learning Engineer interview:
  • Core Java
  • Python full stack
  • Daa science
  • Web Development
Interview preparation tips for other job seekers - Practice makes man perfect don't go back by getting not selected for your dream company be prepared for next one keep challenging yourself.
Interview experience
4
Good
Difficulty level
Easy
Process Duration
More than 8 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed before May 2023. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Explain the latest project you worked on in terms of your role in it.
Round 2 - One-on-one 

(1 Question)

  • Q1. Behavioral and situational questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Be honest with yourself, know your resume in and out. Be confident and friendly with the interviewer and try to be a little curious.

I applied via Recruitment Consulltant and was interviewed in Jan 2022. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. ML algorithms, Live screen share coding
Round 2 - Technical 

(1 Question)

  • Q1. ML deployment, Cloud knowledge

Interview Preparation Tips

Interview preparation tips for other job seekers - Practice atleast one programming language. For ML prefer python. Be prepared with ML algorithms in depth and should have deployment and cloud knowledge.
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via LinkedIn and was interviewed in Jun 2024. There were 4 interview rounds.

Round 1 - Coding Test 

Machine learning - Code K-Means

Round 2 - Coding Test 

Machine Learning - Code Neural Network

Round 3 - One-on-one 

(2 Questions)

  • Q1. Machine Learning Fundamentals
  • Q2. Python Advanced
Round 4 - HR 

(1 Question)

  • Q1. Why this company

Evernorth Health Services Interview FAQs

How many rounds are there in Evernorth Health Services Machine Learning Engineer interview?
Evernorth Health Services interview process usually has 2 rounds. The most common rounds in the Evernorth Health Services interview process are Technical and One-on-one Round.
How to prepare for Evernorth Health Services Machine Learning Engineer interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Evernorth Health Services. The most common topics and skills that interviewers at Evernorth Health Services expect are Artificial Intelligence, C++, Computer Science, Computer Vision and Data Structures.
What are the top questions asked in Evernorth Health Services Machine Learning Engineer interview?

Some of the top questions asked at the Evernorth Health Services Machine Learning Engineer interview -

  1. How to optimize the RAG Pipeli...read more
  2. Types of chunking metho...read more
  3. Managerial questions and few dsa questi...read more

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Software Engineering Advisor
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₹32 L/yr - ₹52 L/yr

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