Series A Startup·Backend Engineer·Onsite - Multi Round
Jul 2026
New grad data science master's student sharing experiences across four companies before landing an offer. Went through a mix of coding screens, onsites, and one team matching process, applied to 1250+ jobs total. Ended up accepting a 155k offer at a data security startup after nearly bombing the DP round.
- Design a Python decorator that rate limits a function.
- Pull data from two live APIs and perform joins and transformations using pandas.
- Given a weighted graph, find the path from source to destination that minimizes the maximum edge weight along the path. Return only the max weight, then also return the actual path. Then, as a follow-up, minimize total edge weight sum as a secondary condition.
- Implement a Trie class that supports adding elements, searching, and caching results. Focus on clean class design.
- You receive a stream of operations as a string containing 'Inc', 'Dec', and 'Reset'. Starting from 0, Inc adds 1, Dec subtracts 1, Reset sets to 0. Return the final value. Follow-up: support compound operations like 'Inc(ResetDec)2', which expands to 'IncResetDecResetDec'.
- Build a trie-based file search system supporting add, remove, and search operations. Then write unit tests for it using AI assistance, and answer system design questions based on your implementation.
- Debug a broken Dijkstra implementation and fix it so it passes a set of provided test cases.
- Implement an LRU cache with a TTL (time-to-live) expiration policy.
- Solve a dynamic programming problem (specific problem not disclosed).
- Solve a problem involving detecting cycles or ordering dependencies in a graph, similar to the course schedule problem.
“This was the Tesla coding screen.”