Overview

  • Each round below will also have questions about values:
    • Snap Core Values:
    • Kind - We listen from the heart, think empathetically, and help each other grow.
    • Smart - We think deeply, question conventions, and strive to never stop learning.
    • Creative - We challenge the status quo to make things with a sense of purpose.
  • 1h coding
  • 1h ML fundamentals
  • 1hr applied ML/ML design
  • 1h system design
  • 1h product-focused
  • 1h leadership / Q&A

Topics

  • LeetCode
  • Design:
    • ML design subscribe to educative
  • Management
    • Frameworks: RICE, SWAT
    • Explainibility of solution and the ROI
    • Prioritization
    • Absorb leadership shit
    • Coaching metrics
    • High/low performer
    • escalations: make sure you are both aware/aligned
      • joint incentives
      • trust
      • company goals
  • ML fundamentals
    • Metrics
    • Online Learning
    • Transformers
    • Go deep, not cursory
    • P(click) design prediction system
    • debugging ML models
    • batch sgd vs sgd
    • batch size
    • what to do when lots of data and low features
    • what to do when lots of features and low data
    • Sample size how to pick
    • learning rate how to pick
    • size in mb, kb
    • how to deal with high engagement with questionable videos
    • attention layers, how many
    • layers, how many
    • param count
    • data diversity
    • vanishing gradients, residual connections
    • architecture good
    • how to add sparsity : wide
    • have issues ready that exist on the team
    • chinchilla google
    • content moderation at input and output
  • Recsys fundamentals but practical applications of each and best used when?
    • Pinterest Transformer by Damien
    • Cold start
    • MAB
    • Warm Start
    • GNN
    • Evaluation
    • Personalization
    • Retrieval
    • Ranking
    • A/B testing
    • Vector embeddings
    • Batch norm, moving average
    • NDCG
    • hashing
    • multitask
    • seasonalit
    • toxicity
    • clustering
    • background
    • NLP
    • Multilayer perceptron
    • ensemble
    • gradient boost
    • SVM
    • Random Forest
    • Eugene Yan recsys
    • wide and deep
    • BIST: Multi armed bandit