ML Engineer

Description

Auto-generated position for ML Engineer

Interview Questions (47)

Q1Can you describe a specific data scraping project you worked on and the technologies you used?
Experience
Q2How do you approach implementing RAG based models, and what challenges have you faced during this process?
Technical
Q3Tell me about a time when you encountered a conflict while working on a team project. How did you handle it?
Behavioral
Q4If you were tasked with scraping a website that frequently changes its structure, how would you adapt your approach?
Situational
Q5What motivates you to work in machine learning, and what are your career goals in this field?
Motivational
Q6How do you approach the implementation of Rag based models in your projects?
Technical
Q7Tell me about a time when you had to work under tight deadlines in a machine learning project. How did you handle it?
Behavioral
Q8If you were tasked with improving the performance of a Rag based model, what steps would you take?
Situational
Q9Can you describe a machine learning project you have worked on from start to finish?
Experience
Q10How would you handle a situation where your model's performance does not meet the expected metrics?
Situational
Q11What machine learning algorithms have you implemented in your past projects, and how did you choose the appropriate one for your task?
Experience
Q12Can you describe a time when you had to work with a team to resolve a disagreement about a technical approach?
Behavioral
Q13What role have you played in the deployment of machine learning models into production?
Experience
Q14If given the opportunity to improve one aspect of your fraud detection system, what would it be and why?
Situational
Q15How do you ensure that your AI models are robust and handle real-world data effectively?
Technical
Q16What is semi-supervised machine learning?
Technical
Q17How do you choose which algorithm to use for a dataset?
Technical
Q18Explain the K Nearest Neighbor algorithm.
Technical
Q19What is feature importance in machine learning, and how do you determine it?
Technical
Q20What is overfitting in machine learning, and how can it be avoided?
Technical
Q21What are the key differences between supervised and unsupervised learning?
Technical
Q22What is a confusion matrix, and why is it useful?
Technical
Q23What is the difference between parametric and non-parametric models?
Technical
Q24What is the bias-variance tradeoff in machine learning?
Technical
Q25Is it true that we need to scale our feature values when they vary greatly?
Technical
Q26The model you have trained has a low bias and high variance. How would you deal with it?
Situational
Q27What is Model Drift and how do you detect it in production?
Technical
Q28Which cross-validation technique would you suggest for a time-series dataset and why?
Technical
Q29Why can the inputs in computer vision problems get huge? Explain it with an example.
Technical
Q30When you have a small dataset, suggest a way to train a convolutional neural network.
Technical
Q31What is the state-of-the-art object detection algorithm YOLO, and how has its architecture evolved recently?
Technical
Q32What is Syntactic Analysis?
Technical
Q33What are Stemming and Lemmatization?
Technical
Q34What are modern techniques to optimize LLM inference speed in production?
Technical
Q35What is an LLM context window, and how do you handle tasks that require more context than the model can take at once?
Technical
Q36How do you mitigate hallucinations in Large Language Models?
Technical
Q37When should you choose Retrieval-Augmented Generation (RAG) over Fine-Tuning?
Technical
Q38What are the steps involved in a typical Reinforcement Learning algorithm?
Technical
Q39What is the difference between Off-Policy and On-Policy Learning?
Technical
Q40Why do we need “Deep” Q learning?
Technical
Q41What is the interpretation of a ROC area under the curve?
Technical
Q42How do you evaluate Generative AI models where there is no single "ground truth"?
Technical
Q43What are the methods of reducing dimensionality?
Technical
Q44How do you find thresholds for a classifier?
Technical
Q45What are the assumptions of linear regression?
Technical
Q46What is the activation function in Machine Learning?
Technical
Q47What is Ensemble learning?
Technical