A QA Engineer at Torc Robotics plays a critical role in the development and deployment of safe, self-driving vehicle technology. Working at the intersection of advanced robotics software and heavy-duty commercial vehicles, you are responsible for validating the software and systems that control Class 8 autonomous trucks. Your work directly impacts the safety of public roads, the reliability of autonomous freight transport, and the strategic goals of Torc Robotics as a key subsidiary of Daimler Truck.

Unlike traditional software quality assurance, QA at Torc Robotics is highly multi-dimensional. It spans virtual simulation environments, Hardware-in-the-Loop (HiL) test benches, and physical vehicle testing on closed tracks and public highways. You will collaborate closely with software developers, systems engineers, and safety experts to design, automate, and execute testing strategies for the autonomous vehicle stack—including perception, localization, path planning, and vehicle control.

This role is intellectually challenging and carries immense responsibility. You are not just looking for minor software bugs; you are identifying complex edge cases and system-level failures where software interacts with physical hardware and unpredictable real-world environments. For engineers passionate about robotics, real-time safety-critical systems, and physical-digital integration, this position offers the chance to work on some of the most advanced engineering challenges of our time.

The following questions are representative of what you can expect during the hiring process. These questions are drawn from real candidate experiences across various QA and system testing teams at Torc Robotics and are grouped by core competency.

C++ and Software Engineering Fundamentals

These questions assess your core programming skills, memory management concepts, and understanding of object-oriented programming, which are vital for writing and reviewing test scripts and automation frameworks in the Torc Robotics codebase.

• Explain the difference between Polymorphism and Inheritance in C++.
• What is Operator Overloading and how would you implement it for a custom data type?

Preparing for an interview at Torc Robotics requires a balanced approach that combines strong software engineering fundamentals with system-level thinking. Candidates who succeed are those who can bridge the gap between abstract code and physical system behavior.

Role-Related Knowledge – You must demonstrate a solid understanding of C++ programming, automated testing methodologies, and robotics fundamentals. Be ready to discuss how you write clean, testable code and how you design frameworks to validate complex software stacks.

Problem-Solving & Systems Thinking – Interviewers will evaluate your ability to break down open-ended, complex testing scenarios. You need to show how you systematically isolate variables, perform root-cause analysis, and design tests that expose critical edge cases in physical-digital systems.

Safety & Quality Mindset – At Torc Robotics, safety is the absolute priority. You must demonstrate a rigorous, detail-oriented mindset where you naturally think about failure modes, redundancy, and risk mitigation in every test plan you discuss.

Collaboration & Communication – Because QA Engineers work closely with cross-functional teams, you must be able to explain technical concepts clearly, present your past projects confidently, and use structured frameworks like the STAR method (Situation, Task, Action, Result) to answer behavioral questions.

The interview process at Torc Robotics is thorough, structured, and designed to evaluate both your technical competence and your alignment with the company's collaborative culture. The process typically takes between three to four weeks from the initial application to the final decision, and candidates frequently report that the team is exceptionally friendly, professional, and communicative.

The journey begins with an initial screening call with a recruiter, followed by a series of rigorous technical assessments that test your software engineering and domain-specific knowledge. If you pass these assessments, you will move on to live interviews with engineers and managers, culminating in a comprehensive panel interview where you may be asked to present your previous projects or research.

The visual timeline above outlines the standard progression of the interview stages for a QA Engineer candidate. While the exact timeline can vary slightly depending on the specific team (such as HiL vs. Vehicle Testing), most candidates will navigate this sequence of screens, assessments, and deep-dive technical panels. Use this timeline to pace your preparation, ensuring you dedicate enough time to both the online assessments and the live presentation preparation.

C++ Programming and Software Quality

Because the core autonomous vehicle stack at Torc Robotics is built on C++ for real-time performance and safety-critical execution, your programming skills will be heavily scrutinized. You must show that you write efficient, robust, and maintainable code.

Be ready to go over:

• Object-Oriented Programming (OOP) – Deep knowledge of inheritance, polymorphism, encapsulation, and abstraction.
• Memory Management – Understanding how to avoid leaks, double-free errors, and segmentation faults, alongside proper use of smart pointers (std::unique_ptr, std::shared_ptr).
• Operator Overloading – Knowing how and when to overload operators to write intuitive and reusable code classes.
• Advanced concepts (less common) – Templates, move semantics, multi-threading basics, and real-time execution constraints.

Example scenarios:

• "Write a C++ class that represents a basic sensor data packet, implementing operator overloading to compare packets by timestamp."
• "Debug a provided C++ code snippet that contains memory leaks or improper pointer usage."
• "Implement a basic algorithm under strict time and space complexity constraints during a live coding session."

Autonomous Vehicle Dynamics & Systems Integration

Testing a self-driving truck requires a deep appreciation of how software commands translate into physical motion. You will be evaluated on your understanding of robotics fundamentals and physical vehicle constraints.

Be ready to go over:

• Vehicle Dynamics – Understanding how mass, velocity, braking capability, and steering geometry differ between passenger vehicles and Class 8 commercial trucks.
• Path and Motion Planning – How autonomous vehicles calculate trajectories, avoid obstacles, and handle lane changes or highway merges.
• Sensor Data Transfer – Knowing how data flows from sensors (LiDAR, RADAR, cameras) through communication buses to the central compute stack.
• Advanced concepts (less common) – Coordinate transformations, localization algorithms (such as Kalman filters), and CAN bus protocol standards (J1939).

Example scenarios:

• "Explain how you would adjust testing parameters for a path planning algorithm when transitioning from a dry highway to a wet, rain-slicked road."
• "How would you design a test to verify that the vehicle control system correctly handles latency in receiving camera data?"
• "Describe the primary differences in spatial awareness requirements between an autonomous car and an articulated truck-trailer combination."

Scenario-Based System Testing

Your core value as a QA Engineer lies in your ability to design robust test strategies for complex, unpredictable real-world environments. Interviewers will present you with open-ended testing challenges to see how you structure your approach.

Be ready to go over:

• Test Automation – Designing scalable test cases that can run automatically in simulation or HiL environments.
• Edge Case Identification – Finding the "unknown unknowns" where multiple system inputs or environmental factors fail simultaneously.
• Physical Diagnostics – Basic troubleshooting of hardware interfaces, including sensors, wiring, and data transfer protocols.
• Advanced concepts (less common) – Fault injection testing, regression testing under limited hardware availability, and safety hazard analysis (ISO 26262).

Example scenarios:

• "You are given a scenario where an autonomous truck fails to detect a pedestrian stepping off a curb behind a parked car. Walk us through how you would isolate, reproduce, and test a fix for this issue."
• "How would you design a test suite to validate the system's response to a sudden, mid-trip failure of a primary LiDAR sensor?"
• "Describe how you would approach testing a software update that affects the truck's automated docking and trailer-coupling maneuvers."

As a QA Engineer at Torc Robotics, your primary mission is to ensure that the autonomous driving system is safe, reliable, and compliant with rigorous performance standards. You will write and execute comprehensive test plans that validate software behavior across multiple platforms, ranging from early-stage simulations to final on-vehicle validation.

Your day-to-day work will involve close collaboration with software development teams to understand new features and design corresponding test strategies. You will develop and maintain automated test scripts, configure HiL test benches, and analyze massive amounts of diagnostic and vehicle log data to identify anomalies. When failures occur, you will perform root-cause analysis to isolate whether the issue stems from a software bug, a hardware malfunction, or a physical integration defect.

In addition to technical testing, you will play an active role in safety reviews and release readiness assessments. You will document test results, track defects, and help define the testing metrics that determine whether a software build is safe to be deployed on public roads. Your work ensures that every autonomous truck powered by Torc Robotics software operates with the highest level of safety and precision.