Tesla Coding Interview Questions
26 Tesla coding interview problems with full optimal solutions — 16 easy, 8 medium, 2 hard. Every problem ships with multiple approaches (brute-force first, then the optimal), complexity tables for each, company-specific tips on what an Tesla interviewer values, and a FAQ section.
Showing 8 problems of 26
- #15mediumfoundational
15. Number of Islands
Count connected land regions in a grid — Tesla uses BFS/DFS grid traversal to reason about how onboard cameras segment obstacle maps and identify distinct occupancy zones during Autopilot scene reconstruction.
- #16mediumfoundational
16. Network Delay Time
Find how long a signal takes to reach all nodes from a source — Tesla applies this shortest-path reasoning to model charging-network latency and route EV fleets to the fastest available Supercharger under real traffic conditions.
- #17mediumfoundational
17. Rotate Image
Rotate an n×n matrix 90 degrees in-place — Tesla's vision pipeline applies this exact transformation when fusing camera frames from different sensor orientations into a unified bird's-eye-view grid for Autopilot.
- #19mediumfoundational
19. Longest Common Subsequence
Find the longest subsequence shared by two strings — Tesla applies this DP pattern when diffing firmware build manifests to identify unchanged module sequences across OTA update versions before deciding what to re-flash.
- #20mediumfoundational
20. Merge Intervals
Collapse overlapping time intervals into a minimal set — Tesla's manufacturing scheduling systems use exactly this algorithm to consolidate overlapping production windows on the Fremont assembly line without leaving idle gaps.
- #22mediumfoundational
22. Course Schedule
Detect whether a set of prerequisite dependencies can be completed — Tesla applies cycle detection on directed graphs when validating ECU (Electronic Control Unit) boot-order dependencies so no firmware module tries to initialize before its required services are ready.
- #23mediumfoundational
23. Jump Game
Decide if you can reach the last index given variable jump sizes — Tesla maps this greedy reachability problem to range estimation for EVs, where each segment has a variable remaining-charge value and you must confirm the destination is reachable before committing a route.
- #24mediumfoundational
24. Subarray Sum Equals K
Count subarrays whose values sum to a target — Tesla uses prefix-sum anomaly detection on vehicle telemetry streams to count windows where cumulative sensor drift exceeds a threshold, triggering a recalibration event in the sensor fusion pipeline.