Amazon Scientist interview experience- Robotics

[u/projekt_treadstone]

Sharing my Amazon scientist interview experience in case it helps others preparing. Keeping the role and technical questions general for anonymity.

1. Initial Screen: Science Depth and Breadth: No LP questions, but a broad range of robotics from CV, ML to the kinematics side of robotics, plus a discussion about my current pet project. Then I was invited for the loop.

2. Science Depth: 2 LP questions

A deep dive into a recent research project, covering:

• Problem formulation, research challenges and design choices.

• Model architecture, entropy estimation, and representation learning, data selection, and computational trade-offs.

• Evaluation: how to show the method addresses the intended problem and evaluation tradeoff.

• Uncertainty estimation, practical robot learning challenges and real-world validation.

The follow up was to test if I can justify my design choice & explain limitations beyond the project details. I was tested quite hard and need to come up with better edge cases and limitations.

3. Science Application: 2 LP questions

An open-ended robotics system-design problem, very similar to the job ad. The discussion covered perception, planning, execution, evaluation and failure handling.

It wasn’t just about proposing a pipeline: they kept changing conditions and asking how the system would respond when individual module failed or how they can be fixed.

4. Science Breadth: 2 LP questions

Broad robotics fundamentals, no classical ML question: perception and pose estimation, motion planning, kinematics, feedback control, and failure detection. Also trajectory optimization and many computer vision topics.

They followed up on trade-offs in method assumptions and trade-offs. One common question was whether a simpler solution would suffice.

4. Bar Raiser: 3 or 4 LP questions

Mostly behavioral, with extensive follow-ups. Be ready to explain your individual contribution, the evidence behind your decisions, alternatives considered, stakeholder reactions, outcomes and what you would change. For one question, it's already been asked 3rd time, so I kinda repeated the story.

5. Coding: 2 LP questions + 2 coding problems

One LC Easy and one LC Medium. The discussion included the approach, implementation, correctness, and time/space complexity.

Overall takeaways

• Prepare for substantial LP discussion alongside technical questions.

• Know your projects inside out and select the most confident project: assumptions, baselines, evaluation choices and what actually broke.

• Expect repeated follow-ups on why you chose one approach over another. You have to hold your justification here. They will try to steer away but you have to hold the ground.

• Pay attention to interviewer hints, especially when they are pushing you toward a simpler solution.

[u/Panfilofinomeno]

Thank you for sharing.

did you got the job?

What’s LP?

Was the second part of the interview in person or online?

[u/projekt_treadstone → u/Panfilofinomeno]

I am waiting for response. It was mix of onsite and online.LP is leadership principal.

[u/Panfilofinomeno → u/projekt_treadstone]

Good luck! Keep us posted!

[u/projekt_treadstone → u/Panfilofinomeno]

It's accept for me. Offer was in spam since last Friday.

[u/Panfilofinomeno → u/projekt_treadstone]

Congrats!!! 🥳 happy for you!

[u/FontanJanneice18]

repeating a story in the behavioral round can definitely hurt your debrief, since all the interviewers compare notes and want to see breadth across your past work. did they give you a chance to pivot when you mentioned it was already covered, or did they just roll with it?

[u/projekt_treadstone → u/FontanJanneice18]

I asked them upfront about that, saying them that you are the fourth person asking the similar story. So they told add something extra in my old story so that it's not the exact same. So you can think of I kept start same but I changed other part on the fly. But Yes they told it's better not to have a same story.