Amazon — Machine Learning Engineer ❌ Failed
Level: Unknown Level
Round: Onsite · Type: Multiple Types · Difficulty: 6/10 · Duration: 240 min · Interviewer: Unfriendly
Topics: Machine Learning Design, Machine Learning Coding, Behavioral Questions, Backtracking Algorithm, Reinforcement Learning, Pre-training, Computer Use Agent
Location: Seattle, WA
Interview date: 2025-12-31
Got offer: False
Summary
Round 1: Machine Learning Design (ML Design)
Question: Design a computer use agent, covering pre-training, post-training, reinforcement learning, and inference.
Round 2: Machine Learning Coding (ML Coding)
Question: Replicate a printed new paper within a notebook environment.
Round 3: Behavioral (BQ)
Question: Standard behavioral questions. The interviewer said they don't emphasize leadership principles.
Round 4: Coding
Question: A LeetCode-style algorithm question. I implemented a backtracking algorithm.
Details
Preparation Tips & Key Takeaways
What I Learned
- The team acquired talent from Adept AI.
- Experience with reinforcement learning and pre-training is crucial for this role.
Recommended Preparation
Machine Learning Design
- Study the design of computer use agents.
- Understand pre-training, post-training, reinforcement learning, and inference techniques.
Machine Learning Coding
- Practice replicating machine learning papers in a notebook environment.
Coding Practice
- Review backtracking algorithms.
Behavioral Questions
- Prepare for standard behavioral questions, but don't heavily focus on leadership principles for this particular team.
Common Pitfalls to Avoid
- Lack of experience with reinforcement learning and pre-training can be a significant disadvantage.
- Not understanding the fundamentals of how reinforcement learning works can lead to rejection.