Axelera AI logo

Growth · Software Engineer Interview Guide

Applies via Ashby

How to Pass the Axelera AI Software Engineer Interview in 2026

The Axelera AI DNA (TL;DR)

Axelera AI values deep technical expertise in AI/ML and hardware-software co-design, emphasizing problem-solving for edge inference challenges. They seek candidates who demonstrate innovation, adaptability, and a strong drive to contribute to their high-performance Metis AI Platform.

The Axelera AI Interview Loop

Your onsite loop will typically consist of 5 rounds.

  1. 1

    Round 1

    Recruiter Screen
    Motivation, role fit, logistics.
  2. 2

    Round 2

    Coding Screen
    LeetCode-medium algorithmic problems under time pressure.
  3. 3

    Round 3

    System Design
    Distributed systems, trade-offs at scale, architecture under constraints.
  4. 4

    Round 4

    Onsite Coding
    LeetCode-hard, debugging, code clarity, edge cases.
  5. 5

    Round 5

    Behavioral / Leadership
    Past evidence of ownership, influence, resolving conflict.

The Danger Zone: Top Reasons Candidates Fail

Based on our database of Axelera AI interview outcomes, avoid these common traps:

  • Inefficiently recalculating the rolling average and standard deviation from scratch for each new data point.
  • Choosing a technology that is too basic or unrelated to the company's domain.
  • Not articulating how their past experience (e.g., embedded systems, performance tuning, compiler work) is relevant.
  • Ignoring the 'stream' aspect and assuming the entire dataset fits in memory.

Test Yourself: Real Axelera AI Questions

Three real prompts pulled from our database.

Type · Conflict Resolution

Describe a situation where you had a technical disagreement with a colleague or manager. How did you approach the discussion, and what was the outcome?

Type · optimization

A core part of Axelera's product involves processing neural network layers. Given a function `process_layer(input_tensor, weights)` that is computationally expensive, write a C++ function `parallel_process_layers(list_of_tensors, weights)` that processes multiple input tensors in parallel using threads. Ensure proper synchronization and efficient workload distribution.

Type · distributed-system

Design a distributed system for collecting and aggregating inference results from thousands of edge devices running Axelera's AI chips. The system needs to handle potentially unreliable network connections and provide near real-time aggregation for monitoring and analysis.

+ many more questions, signals, and worked examples

Sign up to unlock the JobMentis grading rubric

Unlock the rubric →

Axelera AI Interview Question Bank

A sample from our database, grouped by round. Sign up to see the full set.

9 of 20 questions shown

1

Recruiter Screen

1
  1. 1

    Type · motivation

    Axelera AI is developing AI hardware accelerators for edge devices. What interests you about working on the software stack for such specialized hardware, and how does your background align with the challenges of optimizing software for performance-critical, low-power applications?
2

Coding Screen

3
  1. 2

    Type · algorithm

    Given a stream of sensor data (represented as integers) from an edge device, implement a function to detect anomalies. An anomaly is defined as a value that deviates from the recent rolling average by more than 3 standard deviations. You need to efficiently calculate the rolling average and standard deviation. Assume the stream can be very large.
  2. 3

    Type · data-structure

    You are building a system to log events from multiple AI accelerators. Each accelerator generates events with timestamps. Design a data structure that allows you to efficiently retrieve all events within a given time range, sorted by timestamp. Consider the case where events arrive out of order.
  3. + 1 more questions in this round (sign up to unlock)
3

System Design

4
  1. 4

    Type · distributed-system

    Design a distributed system for collecting and aggregating inference results from thousands of edge devices running Axelera's AI chips. The system needs to handle potentially unreliable network connections and provide near real-time aggregation for monitoring and analysis.
  2. 5

    Type · architecture

    Axelera's hardware accelerator requires a specific driver and runtime environment. Design the architecture for this runtime, focusing on how it will interact with the underlying hardware, expose an API for higher-level AI frameworks (like TensorFlow Lite or PyTorch Mobile), and manage resources efficiently on the edge device.
  3. + 2 more questions in this round (sign up to unlock)
4

Onsite Coding

4
  1. 6

    Type · debugging

    You've inherited a C++ codebase for a low-level driver interacting with custom hardware. A bug causes intermittent data corruption, but only under specific, hard-to-reproduce conditions related to timing and interrupt handling. Describe your approach to debugging this issue. What techniques would you employ?
  2. 7

    Type · code-quality

    Write a C++ function to serialize a complex data structure representing a neural network layer's configuration (including weights, biases, activation function type, etc.) into a binary format and deserialize it back. Focus on robustness, error handling, and version compatibility.
  3. + 2 more questions in this round (sign up to unlock)
5

Behavioral / Leadership

8
  1. 8

    Type · Conflict Resolution

    Tell me about a time you had a significant disagreement with an engineering team about a product decision. How did you approach the situation, and what was the outcome?
  2. 9

    Type · Ownership

    Tell me about a time you took ownership of a challenging technical problem that wasn't strictly within your defined role. What steps did you take, and what was the resolution?
  3. + 6 more questions in this round (sign up to unlock)

Unlock the full Axelera AI question bank

Free signup, no credit card. You get every question + the framework, grading signals, and worked answer for each.

Unlock all questions →

Interview tracks at Axelera AI

How Axelera AI's DNA translates across functions. Pick your role.

Compare Axelera AI with similar employers

Same DNA, different bar. Browse the closest companies in our database and see how their loops differ.

Practice Axelera AI interviews end-to-end

FAQ