Micron Technology Interview Questions, Process, and Tips

Q1. First round was with DFT Head. He seemed little arrogant. Asked me basic DFT questions like wrapper architecture, working and how flops will be handled in case of setup and hold.
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Q2. He also asked me about work I have done
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Q1. This was 3 hours back to back interview. In first round, All questions were on scan architecture, need of lockup latches, ATPG Basics, compression architecture etc. Second round was more on the challenges ...read more
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Q1. What were your previous projects that you have worked on
Ans. 
I have worked on projects related to developing software for autonomous vehicles and implementing machine learning algorithms for predictive maintenance.
• Developed software for autonomous vehicles to improve navigation and obstacle avoidance

• Implemented machine learning algorithms for predictive maintenance in manufacturing plants

• Collaborated with cross-functional teams to integrate new technologies into existing systems
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Q2. What all your technical skills and stacks that you have previously used for your projects
Ans. 
I have experience with Java, Python, SQL, AWS, Docker, and Kubernetes in my previous projects.
• Java

• Python

• SQL

• AWS

• Docker

• Kubernetes
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Q1. What is docker and why do we use it for containerising applications
Ans. 
Docker is a platform for developing, shipping, and running applications in containers.
• Docker allows applications to be isolated in containers, making them portable and easy to deploy across different environments.

• Containers share the host OS kernel but run as isolated processes, providing lightweight and efficient virtualization.

• Docker simplifies the process of packaging applications and their dependencies, ensuring co...read more
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Q2. What is database normalisation and how your project benefited from it in the past
Ans. 
Database normalization is the process of organizing data in a database to reduce redundancy and improve data integrity.
• Database normalization involves breaking down data into smaller, more manageable tables and defining relationships between them.

• It helps in reducing data redundancy, improving data integrity, and making the database more efficient.

• For example, in a project I worked on, we normalized the database by spl...read more
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Q1. What has been your experience with challenging projects
Ans. 
I have extensive experience working on challenging projects in various industries.
• Led a team in developing a complex software solution for a major client

• Managed a project with tight deadlines and limited resources

• Implemented innovative solutions to overcome technical obstacles

• Collaborated with cross-functional teams to deliver successful outcomes
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Q2. How would you approach learning about new domain and technologies with a different background
Ans. 
I would approach learning about new domain and technologies with a different background by leveraging my existing skills, seeking out resources, and collaborating with experts in the field.
• Identify key concepts and terminology in the new domain

• Seek out online courses, tutorials, and books to gain foundational knowledge

• Collaborate with colleagues or mentors who have experience in the new domain

• Experiment with hands-on p...read more
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Q1. What is confusion matrix
Ans. 
A confusion matrix is a table that is often used to describe the performance of a classification model.
• It is a matrix with rows representing the actual class and columns representing the predicted class.

• It helps in evaluating the performance of a classification model by showing the number of correct and incorrect predictions.

• It consists of four quadrants: True Positive, False Positive, True Negative, and False Negative...read more
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Q2. Define your project
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Q3. Define principle component analysis
Ans. 
Principal component analysis is a statistical technique used to reduce the dimensionality of data while preserving important information.
• PCA is used to identify patterns in data and express it in a more easily understandable form.

• It works by finding the directions (principal components) along which the variance of the data is maximized.

• These principal components are orthogonal to each other, meaning they are uncorrelat...read more
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Q4. Define inventory policy and inventory control method
Ans. 
Inventory policy is a set of guidelines for managing inventory levels, while inventory control method is the process of implementing those guidelines.
• Inventory policy determines when to order new inventory and how much to order

• Inventory control method involves tracking inventory levels, forecasting demand, and optimizing order quantities

• Examples of inventory policies include Just-in-Time (JIT) and Economic Order Quanti...read more
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Q5. What is reverse logistics
Ans. 
Reverse logistics is the process of moving goods from their final destination back to the manufacturer or point of origin for resale, recycling, or disposal.
• Involves returning products from customers to the manufacturer or retailer

• Includes activities such as returns, refurbishment, recycling, or disposal

• Helps in reducing waste and maximizing value from returned products

• Examples: returning a defective product to the man
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Q1. Pyspark questions on syntax
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Q2. Repartition and coalesce difference
Ans. 
Repartition increases or decreases the number of partitions in a DataFrame, while coalesce only decreases the number of partitions.
• Repartition involves shuffling data across the network, while coalesce tries to minimize shuffling by only creating new partitions if necessary.

• Repartition is typically used when increasing the number of partitions for parallelism, while coalesce is used when decreasing partitions to optimi...read more
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Pyspark, python, sql