Companies rely on machine learning engineers to help design and improve the systems that allow their software to improve on its own, rather than being specifically programmed. During the interview process, be prepared to be tested heavily on both computer science and data science knowledge with an emphasis on recognizing patterns and trends. A bachelor's degree in computer science or a related field will be required.
I really enjoyed the entire process with each and everyone at every stage of the interview. The expectations were very optimistic and mostly focused on the approach of how to tackle when a problem is at hand. 1. Architecture on how to deploy ML models at scale. 2. Deep learning architecture. 3. Building a language model along with approach to building features. 4. Approach to problem solving. 5. Handling disagreement between colleagues.
Name a type of model you typically work on
The 2hr offline technical included a long string comma-separated data. Asked for training a model on the data.
Describe your favourite machine learning algorithm and how it works. What are the weights and what exactly is the input and output of this algorithm,?
what is f1 score in ml
difference btwn AI and ML
types of learning in machine learning
They asked general question about my past experience.
describing how transformers decoders are different from encoders
In-depth Machine Learning
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