Accenture
Global professional services company with leading capabilities in digital, cloud and security.
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
In consulting, you often work with business stakeholders. Tell me about a time you had to explain the results of a complex machine learning model to a non-technical client.
#Stakeholder Management
#Storytelling
Machine Learning Engineer
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Behavioral
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medium
Describe a time when a client or product manager drastically changed the requirements of an ML project halfway through. How did you handle it?
#Client Management
#Agile
Machine Learning Engineer
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Behavioral
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easy
Working at Accenture often means juggling multiple client deliverables. How do you prioritize your tasks when everything seems urgent?
#Prioritization
#Consulting
Machine Learning Engineer
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Behavioral
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medium
Tell me about a time a machine learning model you deployed failed or performed poorly in production. What was the root cause, and how did you fix it?
#Production Failures
#Accountability
Machine Learning Engineer
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Behavioral
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easy
Why do you want to work as a Machine Learning Engineer at Accenture specifically, compared to a traditional tech company?
#Motivation
#Accenture Core Values
Machine Learning Engineer
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Behavioral
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medium
Describe a situation where you had a disagreement with a team member or architect regarding a technical approach (e.g., choosing a specific algorithm or cloud service). How was it resolved?
#Conflict Resolution
#Collaboration
Machine Learning Engineer
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Behavioral
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easy
The AI landscape is moving incredibly fast, especially with Generative AI. How do you stay updated with the latest ML trends and tools?
#GenAI
#Industry Trends
Machine Learning Engineer
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Behavioral
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medium
Tell me about a time you had to build a model using messy, undocumented, or incomplete data provided by a client. How did you proceed?
#Data Quality
#Resilience
Machine Learning Engineer
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Behavioral
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medium
Give an example of how you ensured ethical AI, fairness, or bias mitigation in one of your machine learning projects.
#Responsible AI
#Fairness
Machine Learning Engineer
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Behavioral
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medium
Walk me through a recent machine learning project you took from ideation all the way to deployment. What was your specific contribution?
#End-to-End Delivery
#Project Management
Machine Learning Engineer
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Coding
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easy
Given an array of client transaction amounts and a target sum, write a function to return the indices of the two transactions that add up exactly to the target.
#Arrays
#Hash Map
Machine Learning Engineer
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Coding
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medium
Write a SQL query using window functions to rank the top 3 highest-spending customers per region from a 'sales' table.
#Window Functions
#Ranking
#Aggregations
Machine Learning Engineer
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Coding
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medium
Given a string of user session logs, find the length of the longest substring without repeating characters.
#Strings
#Sliding Window
Machine Learning Engineer
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Coding
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medium
Write a Python script using Pandas to take a dataset with missing values, group by a categorical 'client_industry' column, and impute the missing numerical values with the median of their respective groups.
#Python
#Pandas
#Data Cleaning
Machine Learning Engineer
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Coding
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medium
Given a list of overlapping time intervals representing server downtime, merge all overlapping intervals and return an array of the merged downtimes.
#Arrays
#Sorting
Machine Learning Engineer
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Coding
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easy
Write a SQL query to find all clients who have purchased product A but never purchased product B. Assume a 'clients' table and an 'orders' table.
#Joins
#Subqueries
#Filtering
Machine Learning Engineer
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Coding
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hard
Given a matrix representing a grid of delivery zones with associated costs, write an algorithm to find the minimum cost path from the top-left to the bottom-right zone, moving only right or down.
#Dynamic Programming
#Matrix
Machine Learning Engineer
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System Design
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medium
Design an end-to-end machine learning system to predict customer churn for a telecommunications client.
#Churn Prediction
#End-to-End ML
#Architecture
Machine Learning Engineer
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System Design
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hard
Design a scalable recommendation engine for a large e-commerce client. How would you handle both cold-start problems and real-time user interactions?
#Recommendation Systems
#Scalability
#Real-time Processing
Machine Learning Engineer
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System Design
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medium
Walk me through how you would deploy a trained machine learning model as a scalable API using a cloud provider like AWS (SageMaker) or Azure (Azure ML).
#Cloud
#Deployment
#AWS/Azure
Machine Learning Engineer
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System Design
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hard
Design a real-time credit card fraud detection system. Latency must be under 50 milliseconds.
#Real-time Processing
#Streaming
#Low Latency
Machine Learning Engineer
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System Design
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medium
How would you design a CI/CD pipeline for a machine learning project?
#CI/CD
#Automation
#Testing
Machine Learning Engineer
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System Design
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hard
If a client wants to deploy an open-source LLM (like Llama 3) on their own infrastructure, how would you design the serving architecture to optimize for high throughput and low latency?
#LLM Serving
#Optimization
#Infrastructure
Machine Learning Engineer
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System Design
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medium
Explain how you would use a model registry like MLflow to manage model versions and artifacts across multiple client environments (Dev, QA, Prod).
#Model Registry
#Versioning
#Governance
Machine Learning Engineer
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System Design
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medium
Design an automated document extraction pipeline that takes scanned PDF invoices, extracts key fields, and stores them in a structured database.
#NLP
#OCR
#Pipelines
Machine Learning Engineer
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Technical
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easy
Explain the bias-variance tradeoff. How does it relate to model underfitting and overfitting?
#Model Evaluation
#Theory
Machine Learning Engineer
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Technical
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medium
We are building a fraud detection model for a banking client where fraud cases represent only 0.1% of the data. How would you handle this severe class imbalance?
#Imbalanced Data
#Classification
#Sampling
Machine Learning Engineer
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Technical
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medium
Compare Random Forest and Gradient Boosting Trees. In what scenarios would you choose one over the other?
#Ensemble Methods
#Decision Trees
Machine Learning Engineer
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Technical
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easy
Explain the difference between L1 (Lasso) and L2 (Ridge) regularization. When would you use L1 over L2?
#Regularization
#Linear Models
Machine Learning Engineer
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Technical
•
medium
Accenture is building a knowledge assistant for a client. Explain how Retrieval-Augmented Generation (RAG) works and how you would mitigate LLM hallucinations.
#RAG
#LLMs
#Vector Databases
Machine Learning Engineer
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Technical
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hard
How does the self-attention mechanism work in Transformer models? Walk me through the Query, Key, and Value matrices.
#NLP
#Transformers
#Attention
Machine Learning Engineer
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Technical
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easy
If a client wants to minimize false positives in a medical diagnosis model, which evaluation metric should you optimize for?
#Metrics
#Classification
Machine Learning Engineer
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Technical
•
medium
How do you detect and handle data drift for a machine learning model deployed in production?
#Data Drift
#Model Monitoring
Machine Learning Engineer
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Technical
•
medium
Explain how you would perform cross-validation on a time-series forecasting model.
#Time Series
#Cross-Validation
Machine Learning Engineer
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Technical
•
easy
What are the different strategies for dealing with missing data in a dataset provided by a client?
#Data Preprocessing
#Imputation
Difficulty Radar
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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.