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Accenture Ai Ml Engineer Interview Questions, Process, and Tips

Updated 23 Jan 2025

Top Accenture Ai Ml Engineer Interview Questions and Answers

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Accenture Ai Ml Engineer Interview Experiences

12 interviews found

Ai Ml Engineer Interview Questions & Answers

user image Mithun work

posted on 7 Nov 2024

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
-
Result
No response

I was interviewed in Oct 2024.

Round 1 - Technical 

(3 Questions)

  • Q1. What is OHE ( one hot encoding)
  • Ans. 

    OHE is a technique used in machine learning to convert categorical data into a binary format.

    • OHE is used to convert categorical variables into a format that can be provided to ML algorithms.

    • Each category is represented by a binary vector where only one element is 'hot' (1) and the rest are 'cold' (0).

    • For example, if we have a 'color' feature with categories 'red', 'blue', 'green', OHE would represent them as [1, 0, 0],

  • Answered by AI
  • Q2. What is conditional probability
  • Ans. 

    Conditional probability is the likelihood of an event occurring given that another event has already occurred.

    • Conditional probability is calculated using the formula P(A|B) = P(A and B) / P(B)

    • It represents the probability of event A happening, given that event B has already occurred

    • Conditional probability is used in various fields such as machine learning, statistics, and finance

  • Answered by AI
  • Q3. What is precision, recall
  • Ans. 

    Precision and recall are evaluation metrics used in machine learning to measure the performance of a classification model.

    • Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

    • Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

    • Precision is important when the cost of false positives is high, while recall is i...

  • Answered by AI

Skills evaluated in this interview

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

I applied via Approached by Company and was interviewed in Jul 2024. There were 2 interview rounds.

Round 1 - One-on-one 

(4 Questions)

  • Q1. Explain the ML project you recently worked?
  • Ans. 

    Developed a recommendation system for an e-commerce platform using collaborative filtering

    • Used collaborative filtering to analyze user behavior and recommend products

    • Implemented matrix factorization techniques to improve recommendation accuracy

    • Evaluated model performance using metrics like RMSE and precision-recall curves

  • Answered by AI
  • Q2. Questions related to ML fundamentals like supervised learning, unsupervised learning, evaluation and ML algorithms
  • Q3. Project specific questions
  • Q4. Easy-medium coding questions
Round 2 - HR 

(2 Questions)

  • Q1. What technologies you are working on?
  • Ans. 

    I am currently working on developing machine learning models using Python, TensorFlow, and scikit-learn.

    • Python programming language

    • TensorFlow framework

    • scikit-learn library

  • Answered by AI
  • Q2. How you will approach on machine learning problem?
  • Ans. 

    I would approach a machine learning problem by first understanding the problem, collecting and preprocessing data, selecting a suitable algorithm, training the model, evaluating its performance, and fine-tuning it.

    • Understand the problem statement and define the objectives clearly.

    • Collect and preprocess the data to make it suitable for training.

    • Select a suitable machine learning algorithm based on the problem type (clas...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on your skill and project which you worked on

Skills evaluated in this interview

Ai Ml Engineer Interview Questions Asked at Other Companies

Q1. Can you describe a recent machine learning project you built, inc ... read more
Q2. Do you have any experience with cloud computing, and if so, how w ... read more
Q3. How is data manipulated using NumPy and Pandas, and how did you u ... read more
Q4. What are the basic concepts of Python, including list comprehensi ... read more
Q5. What is deep learning? What is neural network? What are types of ... read more
Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Jul 2024. There were 3 interview rounds.

Round 1 - Assignment 

30 MCQs where 15 Need to be answered correctly to get shortlisted.
Sanfoundary source is very helpful in cracking it.

Round 2 - Technical 

(4 Questions)

  • Q1. Explain Oops concepts
  • Ans. 

    Oops concepts refer to Object-Oriented Programming principles such as Inheritance, Encapsulation, Polymorphism, and Abstraction.

    • Inheritance: Allows a class to inherit properties and behavior from another class.

    • Encapsulation: Bundling data and methods that operate on the data into a single unit.

    • Polymorphism: Ability to present the same interface for different data types.

    • Abstraction: Hiding the complex implementation det

  • Answered by AI
  • Q2. Explain file handling
  • Ans. 

    File handling refers to the process of managing and manipulating files on a computer system.

    • File handling involves tasks such as creating, reading, writing, updating, and deleting files.

    • Common file operations include opening a file, reading its contents, writing data to it, and closing the file.

    • File handling in programming languages often involves using functions or libraries specifically designed for file operations.

    • E...

  • Answered by AI
  • Q3. Explain supervised and unsupervised learning algorithms of your choice.
  • Ans. 

    Supervised learning uses labeled data to train a model, while unsupervised learning finds patterns in unlabeled data.

    • Supervised learning requires input-output pairs for training

    • Examples include linear regression, support vector machines, and neural networks

    • Unsupervised learning clusters data based on similarities or patterns

    • Examples include k-means clustering, hierarchical clustering, and principal component analysis

  • Answered by AI
  • Q4. Coding question on pandas which had 10 followup questions
Round 3 - HR 

(1 Question)

  • Q1. Simple discussion on compensation

Interview Preparation Tips

Interview preparation tips for other job seekers - Easy to moderate interview. Stay focused on basics.

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.

Round 1 - Technical 

(5 Questions)

  • Q1. Describe any NLP project end to end.
  • Ans. 

    Developed a sentiment analysis model using NLP to analyze customer reviews for a product.

    • Collected and preprocessed text data from various sources

    • Performed tokenization, stopword removal, and lemmatization

    • Built a machine learning model using techniques like TF-IDF and LSTM

    • Evaluated the model's performance using metrics like accuracy and F1 score

    • Deployed the model for real-time sentiment analysis of new reviews

  • Answered by AI
  • Q2. What is cosine similarity?
  • Ans. 

    Cosine similarity is a measure of similarity between two non-zero vectors in an inner product space.

    • It measures the cosine of the angle between the two vectors.

    • Values range from -1 (completely opposite) to 1 (exactly the same).

    • Used in recommendation systems, text mining, and clustering algorithms.

  • Answered by AI
  • Q3. What is difference between iterator and iterable?
  • Ans. 

    Iterator is an object that allows iteration over a collection, while iterable is an object that can be iterated over.

    • Iterator is an object with a next() method that returns the next item in the collection.

    • Iterable is an object that has an __iter__() method which returns an iterator.

    • Example: List is iterable, while iter(list) returns an iterator.

  • Answered by AI
  • Q4. Write a python function for cosine similarity.
  • Ans. 

    Python function to calculate cosine similarity between two vectors.

    • Define a function that takes two vectors as input.

    • Calculate the dot product of the two vectors.

    • Calculate the magnitude of each vector and multiply them.

    • Divide the dot product by the product of magnitudes to get cosine similarity.

  • Answered by AI
  • Q5. How did you evaluate your model. what is F1 score.
  • Ans. 

    F1 score is a metric used to evaluate the performance of a classification model by considering both precision and recall.

    • F1 score is the harmonic mean of precision and recall, calculated as 2 * (precision * recall) / (precision + recall).

    • It is a better metric than accuracy when dealing with imbalanced datasets.

    • A high F1 score indicates a model with both high precision and high recall.

    • F1 score ranges from 0 to 1, where

  • Answered by AI

Skills evaluated in this interview

Accenture interview questions for designations

 AI Engineer

 (2)

 ml engineer

 (2)

 Engineer

 (1)

 Software Engineer

 (214)

 Data Engineer

 (78)

 Associate Engineer

 (78)

 Devops Engineer

 (34)

 Test Engineer

 (26)

Interview experience
4
Good
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
No response

I applied via Job Portal and was interviewed in Dec 2024. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Question on random forest and linear regression

Get interview-ready with Top Accenture Interview Questions

Ai Ml Engineer Interview Questions & Answers

user image Hemant Mishra

posted on 9 Oct 2024

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(2 Questions)

  • Q1. What is zip function
  • Ans. 

    The zip function in Python is used to combine multiple iterables into a single iterable of tuples.

    • Zip function takes two or more iterables as arguments and returns an iterator of tuples where the i-th tuple contains the i-th element from each of the input iterables.

    • If the input iterables are of different lengths, the resulting iterator will only have as many elements as the shortest input iterable.

    • Example: zip([1, 2, 3...

  • Answered by AI
  • Q2. What is NLP in Machine learning
  • Ans. 

    NLP (Natural Language Processing) in machine learning is the ability of a computer to understand, interpret, and generate human language.

    • NLP enables machines to analyze and derive meaning from human language data.

    • It involves tasks such as text classification, sentiment analysis, named entity recognition, and machine translation.

    • Examples of NLP applications include chatbots, language translation services, and speech rec

  • Answered by AI

Skills evaluated in this interview

Ai Ml Engineer Jobs at Accenture

View all
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. What are types of prompts?
  • Ans. 

    Types of prompts include text prompts, image prompts, audio prompts, and video prompts.

    • Text prompts: prompts that are in written form

    • Image prompts: prompts that are in visual form

    • Audio prompts: prompts that are in audio form

    • Video prompts: prompts that are in video form

  • Answered by AI
  • Q2. What is the difference between the Symmetric and Asymmetric?
  • Ans. 

    Symmetric encryption uses the same key for both encryption and decryption, while asymmetric encryption uses different keys for encryption and decryption.

    • Symmetric encryption is faster and more efficient than asymmetric encryption.

    • Asymmetric encryption provides better security as it uses a public key for encryption and a private key for decryption.

    • Examples of symmetric encryption algorithms include AES and DES, while ex...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Keep focus on your project explanation

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
More than 8 weeks
Result
No response

I applied via Company Website and was interviewed in Apr 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. About Handling Missing Values
  • Q2. Questions on Embedding

Interview Preparation Tips

Interview preparation tips for other job seekers - Only Round 1 is done. They said you got selected for Round 2 (Final Round) and no call happend. They removed candidature

Ai Ml Engineer Interview Questions & Answers

user image Komal Gaur

posted on 23 Jan 2025

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I was interviewed in Jul 2024.

Round 1 - Coding Test 

Okay asked questions about ML , python , NLP , LLM

Round 2 - One-on-one 

(2 Questions)

  • Q1. Experience or relevancy
  • Q2. Communicate testing

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare using innovative concepts and emerging technologies, then showcase your project.
Interview experience
1
Bad
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Scenario based questions

Accenture Interview FAQs

How many rounds are there in Accenture Ai Ml Engineer interview?
Accenture interview process usually has 1-2 rounds. The most common rounds in the Accenture interview process are Technical, HR and One-on-one Round.
How to prepare for Accenture Ai Ml 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 Accenture. The most common topics and skills that interviewers at Accenture expect are Deep Learning, Machine Learning, Python, Artificial Intelligence and Natural Language Processing.
What are the top questions asked in Accenture Ai Ml Engineer interview?

Some of the top questions asked at the Accenture Ai Ml Engineer interview -

  1. What is the difference between the Symmetric and Asymmetr...read more
  2. what is difference between iterator and iterab...read more
  3. How you will approach on machine learning probl...read more
How long is the Accenture Ai Ml Engineer interview process?

The duration of Accenture Ai Ml Engineer interview process can vary, but typically it takes about less than 2 weeks to complete.

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Accenture Ai Ml Engineer Interview Process

based on 14 interviews

1 Interview rounds

  • Technical Round
View more

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Accenture Ai Ml Engineer Salary
based on 37 salaries
₹7.5 L/yr - ₹27.9 L/yr
42% more than the average Ai Ml Engineer Salary in India
View more details

Accenture Ai Ml Engineer Reviews and Ratings

based on 2 reviews

3.5/5

Rating in categories

4.5

Skill development

4.5

Work-life balance

3.0

Salary

3.0

Job security

3.5

Company culture

2.5

Promotions

3.5

Work satisfaction

Explore 2 Reviews and Ratings
AI / ML Engineer

Gurgaon / Gurugram

2-7 Yrs

Not Disclosed

AI / ML Engineer

Hyderabad / Secunderabad

3-8 Yrs

₹ 7.5-23 LPA

AI / ML Engineer

Bangalore / Bengaluru

3-5 Yrs

₹ 11-20 LPA

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