Just recently concluded Uber The interview process for the 2026 NG SDE position was finalized, and I ultimately received an offer. Thanks to Programhelp for providing the latest mock questions and interview assistance, which helped me avoid many detours during my preparation! As a student in full-time studies, this experience felt very real—juggling coursework, mock tests, and interviews came with considerable intensity but manageable rhythm. In the end, I was able to secure an offer successfully. Here, I write down the complete experience as closely as possible to capture every round’s feelings and details.
OA Phase
Platform: CodeSignal (this being who the majority is referring to)
Questions: 4, 70 minutes
Difficulty: 1 Easy + 2 Medium + 1 Hard
Interview Rounds: 3 Coding + 1 Behavioral
Coding 1
Coding1 is conducted in a similar rhythm to discussing the phone screen, starting with project discussions before moving on to problem-solving. This round focuses more heavily on algorithmic problems and involves a classic variation: given a set of intervals, return the longest overlapping segments. First, they discussed the sweep line approach, then I wrote code based on that. After writing my solution, the interviewer started adding conditions such as handling streaming intervals or supporting deletions. It progressively transformed into a problem more aligned with real-world systems design. This felt like assessing whether I could extend a LeetCode problem to a production-level design.
Coding 2
Coding2 claims to be about Depth in Specialization, but upon actual experience, it primarily involves coding with a bit of design. This round's question was an Object-Oriented Design problem, focusing on designing a ride dispatch system that supports matching between drivers and riders. Initially, several core classes were defined such as Driver, Rider, and Trip. A matching service was then designed. The interviewer would frequently ask why these components were structured this way, for instance, how one might extend the design to support carpooling or where surge pricing should be implemented. What mattered more here was demonstrating effective abstraction and extensibility rather than writing a large amount of code.
System Design
System Design for the Uber Eats home page feed falls under a recurring topic recently. To clarify initial requirements, we first define whether it should be a personalized feed or a generic one feed, and determine latency and QPS (Queries Per Second) expectations. We then provided a classic backend feed architecture: After receiving client requests, they go through the API gateway before reaching the feed service. The feed service fetches data from multiple upstream services such as restaurant service, promotion service, and inventory service. It aggregates and sorts this data based on certain rules, such as distance, ratings, operating hours, promotions, etc., without involving machine learning in sorting.
The interviewer would delve deeply, for example discussing whether the feed is pull-based or push-based. Initially stating that it's pull-based led to questioning under high user loads how to address potential pressures. This discussion then pivoted to a solution involving pre-computation combined with fan-out on write, such as pre-generating portions of feeds for active users and storing them in cache. We also discussed caching strategies; for instance, using Redis for feeds and how invalidation would be handled when restaurants are removed or inventory changes occur. Additionally, we touched upon consistency issues, like what to do if a user sees a restaurant that is already closed. This required performing real-time validation at the read path.
Next we can discuss scaling, such as how to perform a multi-region deployment for global business, ensuring low latency, and maintaining data isolation across different cities. This is a typical backend system design focusing on data aggregation, caching, and scalability, without involving machine learning.
BQ is an abbreviation and lacks context for a full translation. Please provide more information or text to translate.
This round was a bit easier, focusing mainly on collaboration and leadership. For example, they might ask about my experience working with difficult team members or any project management experience I have. The conversation typically revolves around a story of leading a feature rollout where we faced changes in requirements and cross-team communication issues. My manager showed interest in the recommendation system I previously spoke about, and he did some technical deep dive by asking how to handle inconsistencies between offline metrics and online metrics. So while BQ is not completely non-technical, it’s still important to be prepared to switch back to discussing technical details at any time.
Suggestions for Classmate Chen Ning-er
- Practice Test StrategyI've completed over 250 problems on LeetCode Medium difficulty and have solved about 50 on Hard difficulty, with a focus on topics such as Graphs, Dynamic Programming (DP), Heaps, and Design. Uber particularly favors variation problems that include follow-up questions.
- Coding HabitsAlways think aloud by narrating your thought process, providing examples first before writing the code, and finally actively proposing optimizations and edge cases.
- Behavioral preparationPrepare in advance 6-8 high-quality STAR stories, focusing on the following areas: Ownership, Ambiguity, Impact, Team Conflict, and Failure Recovery.
- Time ManagementOA strictly manages time limits, while Onsite reserves 10 minutes per round for optimization and asking questions.
- Mood AdjustmentWhen you are asked and don’t know the answer, don’t panic. You can honestly say, “I’m not 100% sure, but here’s how I would approach it…”. Interviewers actually place more value on your thought process.
- Interview AssistanceIf preparation time is tight and uncertain, some students also choose Real-time interview assistance This approach of voice prompts ensures continuity in my thoughts, especially under high-pressure scenarios like this VO. I even reached out for help from ProgramHelp this time.
Last but not least, I would like to say that although the Uber interview had some pressure, the overall atmosphere was still friendly. The interviewers were generally quite nice. As long as you practice the types of questions and communication beforehand, it's very likely that you will get an offer. Best wishes for a smooth interview process to all seniors in class 26, and may you all secure your dream offers!
