https://github.com/hectorta1989/instacart-machine-learning-engineer-interview
Instacart Machine Learning Engineer Interview
https://github.com/hectorta1989/instacart-machine-learning-engineer-interview
Last synced: 8 months ago
JSON representation
Instacart Machine Learning Engineer Interview
- Host: GitHub
- URL: https://github.com/hectorta1989/instacart-machine-learning-engineer-interview
- Owner: HectorTa1989
- Created: 2022-05-12T07:48:20.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-05-12T07:50:08.000Z (over 3 years ago)
- Last Synced: 2025-01-07T06:47:55.099Z (9 months ago)
- Size: 1.95 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Instacart Machine Learning Engineer Interview
An instamentor mentee Jay recently received a great job offer from Instacart as a Machine Learning Engineer.
Here is what Instacart’s machine learning engineer interview process looked like.
## Instacart Machine Learning Engineer Job Interview Summary
How it gets started: a friend gave an internal referral.
Job Level: Entry-mid
Year of Experience: 2 years experience
Degree: M.S in machine learning
Offer: Yes
TC: ~310K USD
Location: San Francisco, CA
Interview process: 4 weeks
Preparation: 3 months
Has a job: yes
Decide to join: No
## Instacart Machine Learning Engineer Job Interview Round 1: Hiring Manager informational chat:
Deep dive into the past experience, why you leave your current job, and what you see yourself in 5 years.
## Instacart Machine Learning Engineer Virtual Onsite Interview:
## Round 1: Coding and Algorithm
2sum: given an array, find all the 2 elements that sum to 0.
Word count with map-reduce: given a text file, each line is a text string, write a map function and a reduce function to do a word frequency count.
## Round 2: Information Retrieval and Ranking Algorithm
1. Deep dive into past NLP projects.
2. Give me some examples of sparse features and dense features in your NLP projects.
3. Conditional Random Field’s role in sequence tagging, why does it help with LSTM (long short term memory) algorithm’s performance
## Round 3. Machine Learning System Design
Design a ranking system for grocery shopping, e.g., when people search ‘fish,’ how do you rank order all of the fish.
Give me a simple metric to start with.
How would you improve the ranking over time?
What features would you use, and how do we test your model?
## Round 4: Machine Learning Modeling
How do we model a customer’s lifetime value on Instacart?
How do we predict customer churn?
How do you evaluate such a model, cross-validation, how do you explain the AUC curve to non-technical business leaders?
## Round 5: behavioral questions + product design
Tell me about your favorite project, what kind of business problem did you solve, and what is the business impact?
What would you have done differently?
How do you know your solution is the best?
## Offer
Received the job offer one week after the virtual interview.