EY
Ernst & Young Global Limited, a multinational professional services partnership.
4 Rounds
~21 Days
Medium
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Machine Learning Engineer
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Behavioral
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medium
Tell me about a time you had to explain a complex machine learning model to a non-technical stakeholder or client. How did you ensure they understood?
#Stakeholder Management
#Consulting
Machine Learning Engineer
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Behavioral
•
medium
Describe a situation where client requirements changed drastically in the middle of a project. How did you adapt your ML approach?
#Agile
#Client Management
Machine Learning Engineer
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Behavioral
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hard
Tell me about a time your model performed well offline during training but failed or underperformed in production. What was the root cause and how did you fix it?
#Production ML
#Debugging
Machine Learning Engineer
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Behavioral
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easy
Working at EY often involves juggling multiple client engagements. How do you prioritize your tasks when faced with competing tight deadlines?
#Prioritization
#Consulting
Machine Learning Engineer
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Behavioral
•
medium
Describe a time you disagreed with a senior team member or a client regarding a technical approach (e.g., choice of algorithm or architecture). How did you resolve it?
#Conflict Resolution
#Influence
Machine Learning Engineer
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Behavioral
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easy
Why EY? What interests you about working in technology consulting compared to working as an MLE at a traditional tech product company?
#Motivation
#Career Goals
Machine Learning Engineer
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Behavioral
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medium
Tell me about a time you identified a process or pipeline that was highly inefficient and took the initiative to automate or optimize it.
#Process Improvement
#Leadership
Machine Learning Engineer
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Coding
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medium
Given an array of intervals where intervals[i] = [starti, endi], merge all overlapping intervals, and return an array of the non-overlapping intervals that cover all the intervals in the input.
#Arrays
#Sorting
Machine Learning Engineer
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Coding
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medium
Write a SQL query using window functions to calculate the 7-day rolling average of daily transaction volumes for our banking clients.
#Window Functions
#Data Aggregation
Machine Learning Engineer
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Coding
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medium
Using Pandas, how would you efficiently group a dataset of 10 million rows by 'client_id' and find the second highest transaction amount for each client?
#Pandas
#Data Wrangling
Machine Learning Engineer
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Coding
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hard
Write a Python function to compute the TF-IDF scores for a given corpus of financial documents from scratch, without using Scikit-learn.
#NLP
#Math
#Python
Machine Learning Engineer
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Coding
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easy
Given a string containing just the characters '(', ')', '{', '}', '[' and ']', determine if the input string is valid.
#Stacks
#Strings
Machine Learning Engineer
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Coding
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easy
Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target. You may assume that each input would have exactly one solution.
#Arrays
#Hash Table
Machine Learning Engineer
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Coding
•
medium
Given a string s, find the length of the longest substring without repeating characters.
#Sliding Window
#Strings
#Hash Table
Machine Learning Engineer
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Coding
•
medium
Write a Python script using the multiprocessing library to parallelize the downloading and preprocessing of 10,000 images from given URLs.
#Python
#Multiprocessing
#Data Engineering
Machine Learning Engineer
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System Design
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hard
Design an ML system to automatically classify and extract key entities (e.g., vendor, amount, date) from millions of scanned financial invoices.
#NLP
#OCR
#Architecture
Machine Learning Engineer
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System Design
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hard
Design a real-time credit card fraud detection system for a major bank.
#Real-time Processing
#Classification
#Architecture
Machine Learning Engineer
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System Design
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hard
Design a scalable RAG-based chatbot for auditing tax documents. The system must handle thousands of concurrent users and strictly enforce data access controls.
#Generative AI
#RAG
#Security
#Scalability
Machine Learning Engineer
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System Design
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medium
Design a churn prediction system for a telecom client. How would you structure the pipeline from raw data to actionable business insights?
#Predictive Modeling
#Batch Processing
#Business Impact
Machine Learning Engineer
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System Design
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hard
Architect an MLOps pipeline on Azure. Walk me through how code pushed to a repository results in a deployed model.
#MLOps
#Azure
#CI/CD
Machine Learning Engineer
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System Design
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medium
Design a recommendation engine for cross-selling financial products (e.g., credit cards, loans) to existing retail banking clients.
#Recommendation Systems
#Architecture
Machine Learning Engineer
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Technical
•
medium
How do you handle highly imbalanced datasets, such as in a credit card fraud detection model where fraud represents 0.1% of the data?
#Classification
#Data Sampling
#Metrics
Machine Learning Engineer
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Technical
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easy
Explain the difference between Bagging and Boosting. Give an example of an algorithm for each.
#Ensemble Methods
#Random Forest
#XGBoost
Machine Learning Engineer
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Technical
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medium
How does Retrieval-Augmented Generation (RAG) work, and when would you recommend a client use RAG instead of fine-tuning an LLM?
#LLMs
#RAG
#NLP
Machine Learning Engineer
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Technical
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hard
Explain the architecture of a Transformer model. What is the role of self-attention?
#Transformers
#NLP
#Attention Mechanism
Machine Learning Engineer
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Technical
•
medium
What are the key differences between L1 (Lasso) and L2 (Ridge) regularization, and when would you use each?
#Regularization
#Linear Models
Machine Learning Engineer
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Technical
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hard
How do you evaluate an LLM's output for hallucination or factual accuracy in an automated pipeline?
#LLM Evaluation
#MLOps
Machine Learning Engineer
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Technical
•
medium
Explain the vanishing gradient problem in deep neural networks and discuss methods to mitigate it.
#Neural Networks
#Optimization
Machine Learning Engineer
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Technical
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hard
You are running a PySpark job on Databricks to process 5TB of client data, but it keeps failing with OutOfMemory (OOM) errors. How do you troubleshoot and optimize it?
#PySpark
#Databricks
#Distributed Computing
Machine Learning Engineer
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Technical
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medium
What is Data Drift vs Concept Drift? How do you monitor for them in a production ML system?
#Model Monitoring
#Production ML
Machine Learning Engineer
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Technical
•
medium
Explain how you would containerize a Python-based ML model using Docker and deploy it as a REST API.
#Docker
#API
#Deployment
Machine Learning Engineer
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Technical
•
medium
How does XGBoost handle missing values internally?
#XGBoost
#Algorithms
Machine Learning Engineer
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Technical
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easy
Explain the trade-off between precision and recall. Which is more important in medical diagnosis vs spam detection?
#Metrics
#Evaluation
Machine Learning Engineer
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Technical
•
medium
What are vector embeddings, and how do you store and query them efficiently at scale?
#Embeddings
#Vector Databases
Machine Learning Engineer
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Technical
•
medium
How do you ensure fairness and mitigate bias in machine learning models, especially for models used in HR or lending?
#Ethics
#Bias
#Fairness
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Think Out Loud
Always explain your thought process before writing code or drawing architecture.