Katkat

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Aurora interview questions

5 practice questions in the style of Aurora's interviews, covering ML System Design, Coding & Algorithms, Behavioral & Leadership.

Questions5

0 easy2 medium3 hard

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Aurora interview questions by the numbers

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Katkat has 5 Aurora interview questions. The largest topics are Coding & Algorithms (60%), Behavioral & Leadership (20%) and ML System Design (20%). By difficulty: 40% medium and 60% hard. The most common round is Technical Screen (100%).

Difficulty

  • Medium40% · 2
  • Hard60% · 3

Interview rounds

  • Technical Screen100% · 5

Roles

  • Software Engineer60% · 3
  • Machine Learning Engineer40% · 2

Showing 1–5 of 5 results

  • An open-ended ML system design discussion on how large language models and vision-language models could be used in autonomous driving, including whether one could actually drive the vehicle. It tests mapping off-board and on-vehicle uses, containing hallucination and latency in a safety-critical stack, and planning evaluation.

    AuroraMachine Learning EngineerML System DesignTechnical Screen
  • This question evaluates a candidate's understanding of streaming algorithms and efficient data-structure techniques for maintaining sliding-window minima, measuring competency in algorithmic thinking, time and space complexity, and online processing.

    AuroraSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Evaluate arithmetic expressions containing non-negative integers and the four basic operators without using eval. Preserve precedence and left associativity, implement division that truncates toward zero, and process expressions up to 300,000 characters efficiently.

    AuroraSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of C++ resource management, ownership semantics, RAII, and reference counting implementation within the coding and algorithms domain, emphasizing pointer semantics and object lifetime.

    AuroraSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A leadership question asking how you would present an initiative to bring language models into a self-driving program to leadership and win scope for it. It tests problem framing, gathering evidence, handling risk in a safety-critical organization, aligning stakeholders, and making a concrete, phased ask.

    AuroraMachine Learning EngineerBehavioral & LeadershipTechnical Screen

Aurora interview experiences

All 1 →
  • Grilled on Using LLMs to Drive Self-Driving CarsAurora · Machine Learning Engineer · Senior+ · Technical Screen · Sep 2026

    I interviewed with Aurora for an MLE role. Overall the questions were pretty middle-of-the-road and not really that hard. Maybe I just wasn't prepared enough and didn't manage to wow them. The senior package can only go up to about 500k at most, which maybe isn't all that attractive either. The question that came up the most in the interviews was how to use LLMs in autonomous driving, how to use…

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