Applied Intuition Software Engineer Interview Questions + Guide in 2025

Applied Intuition is at the forefront of developing simulation and infrastructure tools critical for the safe and rapid advancement of autonomous systems. It is highly regarded in the tech world and trusted by 18 of the top 20 automakers, including Daimler Torc, Nissan, Toyota, and Volkswagen Group.

The global software-defined vehicle market size was valued at $49.3 billion in 2024 and is estimated to register a CAGR of 25.2% between 2025 and 2034. As demand for autonomous technology increases, Applied Intuition software engineers are at the core of this transformation. They develop scalable systems, optimize real-time data processing, and collaborate with talented engineers and experts to push the boundaries of AI technology.

If you are passionate about cutting-edge technology and the future of autonomous vehicles, applying for a software engineering role at Applied Intuition presents an exciting opportunity. The company fosters a culture of continuous innovation, provides a comprehensive platform for engineers to excel, and offers competitive compensation.

In this guide, we will cover the interview process and common Applied Intuition software interview questions to help you navigate the interviews successfully.

Software engineers at Applied Intuition design tools and platforms that support autonomous vehicle (AV) and advanced driver-assistance systems (ADAS) development. Automotive companies use this platform to conduct virtual testing of autonomous systems, perform large-scale simulations, and validate ADAS and AD systems for safety and regulatory compliance.

Engineers from different specializations, such as simulation, application engineering, and embedded systems, work together to refine and enhance the platform. They also engage in customer-facing problem-solving, making sure Applied Intuition’s products integrate seamlessly into real-world applications.

Some key areas they contribute to include:

• Vehicle Simulation (VehicleSim): Creating physics-based models that accurately replicate real-world vehicle behavior for AV and ADAS testing.
• Operating Systems & Infrastructure: Building scalable backend systems that power simulation platforms, enabling automotive companies to rapidly iterate on their AV designs, test edge cases, and ensure safety compliance before real-world deployment.
• Sensor Simulation: Developing realistic sensor models (LiDAR, radar, cameras) that help AVs interpret a wide range of simulated environments and conditions.
• Mapping & Perception: Designing tools that generate high-definition maps and validate perception algorithms used in AV navigation, ensuring accurate environmental understanding in diverse real-world conditions.
• Scenario Generation & Testing: Automating the creation of real-world driving scenarios to test AV decision-making under a vast array of potential scenarios, including edge cases that might be rare or dangerous to test in physical environments.

Their work ensures that AV developers can safely and efficiently train, test, and deploy autonomous systems before hitting real roads.

Qualifications

Applied Intuition seeks candidates for software engineering roles who can effectively contribute to its mission in the autonomous vehicle industry. The following qualifications are required for the role:

Must Have

• Bachelor’s degree in computer science, engineering, or a related field.
• 2–4 years of software development experience.
• Proficiency in programming languages such as C++, Python, Java, or JavaScript.
• Experience with algorithm analysis and software development practices.

Nice to Have

• Advanced degrees (MSc or PhD) in relevant fields.
• Experience with safety-critical software development.
• Knowledge of machine learning techniques.

Applied Intuition hires software engineers at different seniority levels, ranging from entry-level to senior positions, with some specializations open to all levels of experience. Compensation can range from $123,000 to $446,000 per year, depending on experience and location.

The interview process at Applied Intuition is structured and quite challenging. It focuses on both technical abilities and cultural fit. Typically, the interview involves the following stages:

1. Initial Screening (30 minutes)

   The process starts with a recruiter’s phone screen or via video call. This interview is primarily behavioral, focusing on personal and past experiences. There may also be a light technical discussion covering your skills and problem-solving abilities.

2. Technical Screening (45 minutes each)

   In this stage, candidates usually face multiple rounds of technical interviews, often 2 or 3 rounds. These involve medium-level live coding and system design problems to assess their technical proficiency and understanding of software engineering principles.

3. On-site Interview

   The on-site interview includes back-to-back technical rounds, starting with a group introduction with multiple interviewers. Candidates usually undergo 3 to 4 technical interviews, covering coding, system design, and problem-solving. There may also be a behavioral or culture-fit interview to assess alignment with the company’s values.

The Applied Intuition software engineer interview spans various topics. The interview questions are designed to assess a candidate’s problem-solving abilities and technical expertise. Generally, the most frequently asked topics are in the following areas:

• Algorithms
• System Design
• Python
• Machine Learning
• Behavioral Questions

Applied Intuition Software Engineer Algorithm Questions

The ability to write optimized, efficient code and think through challenging scenarios is a core requirement for the role.

1. Write a function that converts an N-dimensional nested list of integers into a 1D list. The input can have any level of nesting, and the output should be a flattened list of all elements.

You can use recursion to handle the different levels of nesting. The idea is simple: whenever you encounter a list, recursively flatten it. If you find an integer (or any non-list element), add it to the result list.

2. Given an integer list nums with length n and an integer target, find three integers in nums that yield a sum closest to the target.

Sorting the list first might help, and from there, consider using a two-pointer approach to efficiently explore different sum combinations.

3. Write a function that checks if a given binary tree is a valid binary search tree (BST).

You have a binary tree and need to check if it follows the BST rules: every node’s left child must have a smaller value, and every right child must have a larger one. A common approach is using in-order traversal while keeping track of previous values.

4. Write a function max_substring that returns the longest common substring between two given strings, string1 and string2.

This problem is closely related to dynamic programming, but there are other approaches too. Create a table to store the length of the longest common suffix for each pair of characters. By iterating through the strings, you can build up the longest common substring efficiently.

Applied Intuition Software Engineer System Design Questions

In the Applied Intuition software engineer interview, system design questions assess a candidate’s ability to architect scalable and efficient systems. These questions often focus on real-time data processing, simulations, and autonomous vehicle operations, reflecting the challenges of building reliable and high-performance systems.

5. How would you design a system that allows autonomous vehicles to communicate with each other to share data, such as traffic conditions, obstacles, or route changes?

Autonomous vehicles need to share real-time data like traffic conditions, obstacles, and route changes. A robust system must ensure low latency, high reliability, and security while handling network failures. Consider using vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) protocols to enable seamless communication.

6. Discuss the architecture for a simulation platform that allows testing of autonomous vehicle algorithms in various scenarios.

A strong simulation platform must replicate real-world driving conditions, including traffic, weather, and road obstacles. Think about how to make the system scalable for running multiple tests at once while integrating sensor modeling and AI-driven behavior simulation.

7. Describe how to design a system that sends notifications to users based on specific events or triggers.

A notification system must detect key events and send alerts in real time. Start by defining what triggers an alert, system logs, or external APIs. Then, decide how to deliver notifications (email, SMS, or push alerts) while ensuring the system can scale efficiently for a large number of users.

8. Create a scalable backend for storing and analyzing terabytes of log data from autonomous vehicle test simulations.

AVs generate massive amounts of sensor, driving, and simulation data. When answering this, make sure you don't give a weak answer like *"I would store all AV logs in an SQL database and use basic queries to analyze them."* Instead, highlight how logs are accessed, discuss data partitioning and compression, and explain scaling strategies.

9. Design a real-time anomaly detection system for autonomous vehicle fleet monitoring.

A robust anomaly detection system for an AV fleet should monitor sensor readings, vehicle diagnostics, and driving behavior in real time. Don't give a too simplistic answer that doesn't define what counts as an anomaly, like inconsistent GPS data. You need to make sure that your answer is as detailed as possible, such as discussing the machine learning models you'd use or if you’d use a hybrid approach. 

Applied Intuition Software Engineer Python Questions

Python is widely used in autonomous vehicle technology for data processing, simulations, and system development. In the Applied Intuition interview, Python questions assess your coding proficiency, understanding of core concepts, and ability to write efficient, maintainable code.

10. Find and return all the prime numbers in an array of integers.

To solve this, you need to check if each number in the array is prime. A basic approach would be to iterate through the list and test divisibility. You can check divisibility up to the square root to make your solution more efficient.

11. Given a dictionary where keys are strings and values are numbers (which may have duplicates), write a function to extract the unique values that appear only once.

Since dictionary values can repeat, you need to track how often each value appears. You can use a counter or another dictionary to count occurrences. Once you have that, just pick the values that appear only once.

12. Write a function group_anagrams that takes a list of words and groups them into lists of anagrams, where each group contains words that share the same letters in a different order.

Anagrams have the same letters, just in a different order. To group them, you can sort the letters in each word or use a hash map to create a common key for words with the same characters.

13. Given a string, find the first non-repeating character in it and return its index. If it doesn’t exist, return -1.

To find the first unique character, keep track of how often each character appears while maintaining their order. You can use a dictionary to count occurrences, then scan the string again to find the first character that appears only once.

Applied Intuition Software Engineer Machine Learning Questions

Machine learning is a key area for evaluating a candidate’s understanding of core concepts and their ability to apply these techniques in the complex world of autonomous vehicles. It’s all about thinking critically and solving real-world challenges using the right machine learning methods for innovative solutions.

14. What does it mean to use “inception architecture” for a convolutional neural network?

Inception architecture in CNNs uses multiple filter sizes within the same layer to capture different features. By applying 1x1, 3x3, and 5x5 filters in parallel, the model learns various patterns at different scales.

15. How would you apply reinforcement learning to improve decision-making for autonomous vehicles in dynamic environments?

Reinforcement learning helps autonomous vehicles improve decision-making by learning from trial and error. The vehicle is trained to take actions based on rewards, optimizing for the best outcomes, like avoiding obstacles and choosing the safest, most efficient route.

16. Explain how CNNs can be applied to autonomous vehicles, particularly in the context of image recognition.

CNNs are ideal for processing visual data from cameras for tasks like object detection, lane detection, and obstacle avoidance. When answering this question, think about how CNN layers help break down an image into smaller features, enabling the vehicle to recognize and react to the environment in real time.

17. How do you balance the bias-variance tradeoff when building a machine learning model?

The bias-variance tradeoff is about finding the right model complexity. High bias leads to underfitting, while high variance causes overfitting. Think about techniques like cross-validation or regularization to manage the tradeoff effectively and ensure your model generalizes well.

Applied Intuition Software Engineer Behavioral Questions

Behavioral questions at Applied Intuition focus on evaluating how well you can handle real-world challenges, communicate effectively, and collaborate within a team.

18. Why did you apply to our company?

When answering this, think about what excites you about the company’s mission, culture, and the work they do. Talk about how your values align with theirs and how your skills can contribute to their goals. 

19. Tell me about a project in which you had to clean and organize a large dataset.

Describe a situation where you worked with messy or unstructured data. Highlight the techniques you used to clean and organize the data and why they were essential for the project’s success. 

20. Describe an analytics experiment that you designed. How were you able to measure success?

Explain an experiment where you applied a structured approach to analyzing data like A/B testing or another method. Talk about what metrics you used to track success and how the results led to actionable insights or decisions.

21. Describe a data project you worked on. What were some of the challenges you faced?

Discuss a project where you had to work with complex data. Focus on the challenges you encountered, like large data volumes or data quality. Describe how you overcame these challenges and what you learned from the experience.

22. Tell me a time when your colleagues did not agree with your approach. What did you do to bring them into the conversation and address their concerns?

Share an example where you disagreed with a colleague or team member about a solution or approach. Highlight how you communicated effectively to understand their perspective and how you found common ground or a compromise.

Securing a software engineering role at Applied Intuition is no small feat. Their interview process assesses not only your technical expertise but also your ability to innovate and think critically within the complex world of autonomous vehicles. With limited resources available, let this article serve as your guide. Use the questions to review essential concepts, and feel free to explore more. Practicing through mock interviews can also be a great help. Check out our learning paths and additional resources on our website. Best of luck as you prepare for one of the most exciting roles in tech!