eugeneyan.com posted an interesting article about how they interview machine learning and artificial intelligence engineers. That post can be found HERE. I feel this is useful for anybody looking to apply for these roles. Key points I found interesting are the following
The technical skills they are looking for are the following: Note its equally as important as how the candidate uses these skills meaning they are interested in how they think.
- Check if 2/3D arrays meet predefined criteria (e.g., validating robot’s simulated route through a warehouse), checking for edge cases, and writing unit tests
- Implement and start an inference endpoint, including input/output validation, logging, monitoring, and command to update endpoint state
- Build a pipeline to process data, first in batch and then adapting it for streaming
Understanding of data literacy. They use these questions to test this concept
- How did you wrangle the data? What issues did you face and how did you fix them?
- What was a misleading summary statistic? Which were more useful than others?
- What was an insightful data viz you created and why? What was the least helpful?
How the candidate deals with output of opaque models
Showing a basic understanding of evals meaning how models are evaluated.
For not technical skills, they look for ambiguity, influence, complexity, and execution (AICE)
Get these details from the post found HERE.