Skip to contentSkip to footer

Ai Software Engineer Interview Questions

Salaries
Interviews

5,961 ai software engineer interview questions shared by candidates

1. Online Assessment (OA) The process often begins with an online test if you’re applying through campus recruitment or general hiring platforms. Typical components: Coding challenges on platforms like Codility or HackerRank (e.g., data structures, algorithms, problem-solving). Machine learning questions, such as: Model evaluation (precision, recall, F1-score, AUC) Data preprocessing and feature engineering Bias-variance tradeoff Sometimes, a case-based or applied AI problem, e.g., “How would you detect spam messages?” 2. Technical Screening / Recruiter Call A recruiter or technical interviewer gives you an overview of the role and checks your alignment. What to expect: Discussion of your AI/ML projects, especially real implementations or research. Questions about your experience with frameworks (PyTorch, TensorFlow, Azure ML). Basic checks on your knowledge of Azure AI services, since Microsoft focuses heavily on Azure. 3. Technical Interviews (1–2 rounds) You’ll meet with engineers or data scientists who will dive deeper into your technical capabilities. Topics Covered: Coding & Problem Solving: Writing clean, efficient Python code; using libraries like NumPy or Pandas. Machine Learning & Deep Learning: Understanding of ML algorithms (e.g., regression, decision trees, clustering). Neural network concepts (CNNs, RNNs, Transformers). Model evaluation and optimization techniques. AI System Design: How you’d design an end-to-end ML pipeline. Handling data at scale using Azure tools (Data Lake, Blob Storage, ML Studio, etc.). Case Study Example: “You’re asked to build an AI system that detects product placement in images (object detection). How would you collect data, train the model, evaluate results, and deploy it?” They’ll look for clarity, structured reasoning, and awareness of trade-offs. 4. Technical Discussion / Team Interview This is often a deep dive into one of your projects — for example, something on your CV. You might be asked: Why you chose a certain model architecture (e.g., YOLO vs. Faster R-CNN). How you handled data preprocessing, imbalance, or evaluation. How you ensured efficiency and scalability (e.g., using async I/O or chunking large datasets). They might also discuss your approach to experimentation and reproducibility in ML workflows.
avatar

ML/AI Engineer

Interviewed at Microsoft

4★
Oct 26, 2025

1. Online Assessment (OA) The process often begins with an online test if you’re applying through campus recruitment or general hiring platforms. Typical components: Coding challenges on platforms like Codility or HackerRank (e.g., data structures, algorithms, problem-solving). Machine learning questions, such as: Model evaluation (precision, recall, F1-score, AUC) Data preprocessing and feature engineering Bias-variance tradeoff Sometimes, a case-based or applied AI problem, e.g., “How would you detect spam messages?” 2. Technical Screening / Recruiter Call A recruiter or technical interviewer gives you an overview of the role and checks your alignment. What to expect: Discussion of your AI/ML projects, especially real implementations or research. Questions about your experience with frameworks (PyTorch, TensorFlow, Azure ML). Basic checks on your knowledge of Azure AI services, since Microsoft focuses heavily on Azure. 3. Technical Interviews (1–2 rounds) You’ll meet with engineers or data scientists who will dive deeper into your technical capabilities. Topics Covered: Coding & Problem Solving: Writing clean, efficient Python code; using libraries like NumPy or Pandas. Machine Learning & Deep Learning: Understanding of ML algorithms (e.g., regression, decision trees, clustering). Neural network concepts (CNNs, RNNs, Transformers). Model evaluation and optimization techniques. AI System Design: How you’d design an end-to-end ML pipeline. Handling data at scale using Azure tools (Data Lake, Blob Storage, ML Studio, etc.). Case Study Example: “You’re asked to build an AI system that detects product placement in images (object detection). How would you collect data, train the model, evaluate results, and deploy it?” They’ll look for clarity, structured reasoning, and awareness of trade-offs. 4. Technical Discussion / Team Interview This is often a deep dive into one of your projects — for example, something on your CV. You might be asked: Why you chose a certain model architecture (e.g., YOLO vs. Faster R-CNN). How you handled data preprocessing, imbalance, or evaluation. How you ensured efficiency and scalability (e.g., using async I/O or chunking large datasets). They might also discuss your approach to experimentation and reproducibility in ML workflows.

1. A generic online IQ/Pattern Matching quiz, for which you can easily find examples online 2. A set of online logic tests, 30 minutes each. They range from traditional text comprehension to measuring analytics skills. No specific background required, but a little probability background can help, along with keeping an Excel sheet under hand. I found them quite enjoyable and stimulating, tbh. 3. Other online tests. 2 coding problems, where you can use whatever language you want. 1h each. One personality questionnaire, where you have to answer some more traditional HR questions 4. First HR interview 5. A live problem solving interview, where I had to solve 2 logic problems 6. Another HR interview, similar to (4) but with a different interviewer 7. A technical interview specific to your role After that, you might have to do more technical interviews, or have a chat with other teams. It really depends on how well you scored in the previous steps and how well you fit in the position you applied for.
avatar

AI Researcher

Interviewed at Bending Spoons

4.7★
Feb 26, 2022

1. A generic online IQ/Pattern Matching quiz, for which you can easily find examples online 2. A set of online logic tests, 30 minutes each. They range from traditional text comprehension to measuring analytics skills. No specific background required, but a little probability background can help, along with keeping an Excel sheet under hand. I found them quite enjoyable and stimulating, tbh. 3. Other online tests. 2 coding problems, where you can use whatever language you want. 1h each. One personality questionnaire, where you have to answer some more traditional HR questions 4. First HR interview 5. A live problem solving interview, where I had to solve 2 logic problems 6. Another HR interview, similar to (4) but with a different interviewer 7. A technical interview specific to your role After that, you might have to do more technical interviews, or have a chat with other teams. It really depends on how well you scored in the previous steps and how well you fit in the position you applied for.

Viewing 5791 - 5800 interview questions

Glassdoor has 5,961 interview questions and reports from Ai software engineer interviews. Prepare for your interview. Get hired. Love your job.