How I Got a 6-Month SDE Internship+ PPO at Uber (OA + 2 Interview Rounds)

How I Got a 6-Month SDE Internship at Uber (1.87L stipend)

After attempting 50+ Online Assessments and going through 5+ technical interviews, I finally received an offer from Uber for a 6-month Software Development Engineer (SDE) Internship with PPO opportunity.

This is not a “perfect journey” story.
It’s a realistic one: full of attempts, rejections, learning curves, and one interview I genuinely thought I had not cleared.

In this post, I’ll share:

My OA experience, Both interview rounds, What actually mattered, Why I still got selected even with an incomplete solution


🧪 Uber Online Assessment (HackerRank)

The OA had 3 DSA problems to be solved in 65 minutes.

First two ≈ LeetCode Medium → solved in ~25 minutes
Third ≈ LeetCode Hard → passed 9/15 test cases
Submitted in ~40 minutes

At first I thought partial solution = rejection.
But A few days later → interview call.


🎯 Interview Format

There were 2 technical rounds and both followed the same pattern:

Introduction → Behavioral (~10 min) → DSA Problem → Discussion

The behavioral part actually mattered.
Questions were around teamwork, conflicts in projects, and decision making.
This wasn’t a formality — they were evaluating communication and ownership.


💡 Round 1

The first round had a HashMap-based problem. The tricky part was not implementation but properly understanding the problem statement and identifying edge cases.

I began with a brute force approach, explained why it would fail, and gradually moved toward an optimized solution while discussing time and space complexity. Most of the interview became a discussion rather than coding. Only in the final 15 minutes I implemented the solution, and it worked on the first run. The interviewer seemed satisfied and the round ended positively.

What stood out to me was that the interviewer cared far more about reasoning than syntax.


🔥 Round 2 — The One I Thought I Failed

The second round was significantly harder.

A grid was given where 0 represented empty cells, 1 represented poisonous gas spreading every second in four directions, and 2 represented walls. The task was to determine the maximum time a person could wait at (0,0) and still safely reach (n-1,m-1).

(Question Link in the comments)

The intended solution involved multi-source BFS combined with binary search on the answer.

I explained my intuition, derived a brute force idea, and then proposed the optimal approach. However, the discussion itself took more than 35 minutes, leaving only about 10-15 minutes to code a large solution. My code compiled and ran but produced incorrect output due to small logical mistakes.

I asked the interviewer if I could debug this code, but they said that: It's okay, we have less time. (After the interview, I realized the bugs were minor and easily fixable.)

After this, they asked a few questions about my projects in the resume, especially in AI/Deep Learning.

After the interview, I was almost certain I would be rejected.

But I still received the offer.


🧠 What I Actually Learned

Uber was not evaluating perfect code or memorized questions. The interviewers were evaluating clarity of thought, communication, and how I approached an unfamiliar problem. My implementation was incomplete, but my reasoning and direction were correct, and that mattered more.

The biggest realization for me was simple:

Interviews are not LeetCode contests.

A candidate who clearly explains a correct approach can outperform someone who writes fast code but cannot reason about it.

You don’t need a perfect interview.
You need a convincing one.


💬 Open Discussion

If you have interned at Uber, I’d really appreciate your guidance.

I’d love to know how interns can maximize their chances of getting a PPO, what I should start learning or revising before the internship begins, and what kind of work expectations I should realistically prepare for. I’m also curious about the perks, benefits, and overall intern experience at the company.

Any advice, tips, or personal experiences would genuinely help — not just me, but also others preparing for similar opportunities.

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