The questions listed above represent the core technical and behavioral pillars of the evaluation process. When preparing, do not simply memorize solutions; instead, focus on explaining your underlying methodology, discussing trade-offs, and demonstrating a structured approach to problem-solving.

To pass the rigorous technical bar at Torc Robotics, your preparation must be structured and comprehensive. You cannot rely solely on standard software engineering prep; you must adapt your study plan to address the unique intersection of systems software, physical dynamics, and safety engineering.

When organizing your preparation, focus on demonstrating strength across these key evaluation criteria:

Role-Related C++ & Systems Knowledge – You must possess a deep, intuitive understanding of C++ (specifically C++14 and newer). This includes master-level knowledge of the Standard Template Library (STL), smart pointers, memory management, and multi-threading. You should be able to write clean, idiomatic C++ code on a whiteboard or virtual editor without relying on IDE auto-complete.

Analytical & Mathematical Problem-Solving – For autonomy-focused roles, you need to brush up on vector calculus, linear algebra, coordinate transformations, and basic physics (kinematics and dynamics). Interviewers want to see that you can translate physical constraints and mathematical formulas directly into efficient code.

Systems & Safety-Critical Design – You must be able to design systems that are modular, testable, and robust against failures. Understand how to design for low latency, how to handle edge cases in hardware communication, and how to apply functional safety principles to software architecture.

Culture Fit & Safety Mindset – Torc Robotics operates in an industry where software bugs can have catastrophic real-world consequences. You must demonstrate a disciplined approach to testing, a strong sense of personal accountability, and a collaborative communication style that prioritizes safety over cutting corners.

The interview process at Torc Robotics is designed to evaluate both your technical depth and your alignment with the company’s safety-first culture. Candidates can expect a multi-stage journey that typically spans three to six weeks from initial contact to final decision. The process is thorough, demanding, and highly focused on practical engineering skills rather than abstract academic puzzles.

Typically, the process begins with an initial recruiter screen to discuss your background, followed by one or more technical Online Assessments (OAs) on platforms like HackerRank. If you pass the OAs, you will move to a technical phone or video screen (often using CodePair) where you will write code live with an engineer. The final stage is a comprehensive virtual or on-site loop consisting of multiple panels focusing on coding, system design, behavioral attributes, and managerial fit.

This visual timeline outlines the typical path a candidate takes through the hiring funnel. While the sequence of stages is highly standardized, the specific content of the technical assessments and loop panels will be tailored to the seniority and specialization of the role you are targeting. Use this timeline to pace your preparation, ensuring you are fully prepared for live coding and system design by the time you complete the online assessments.

C++ Fundamentals and Low-Level Systems

At Torc Robotics, C++ is the language of choice for real-world execution. You will be evaluated on your understanding of how the language interacts with the underlying operating system and hardware.

Be ready to go over:

• Memory Management – Stack vs. heap allocation, custom allocators, preventing memory leaks, and the mechanics of smart pointers (std::unique_ptr, std::shared_ptr, std::weak_ptr).
• Object-Oriented Programming & Inheritance – Virtual tables (vtables), virtual destructors, multiple inheritance pitfalls, and resource management via RAII.
• The STL and Modern C++ – Efficient use of containers (e.g., std::vector vs. std::list), move semantics, rvalue references, and lambda expressions.
• Advanced concepts (less common) – Cache locality, lock-free programming, real-time operating system (RTOS) constraints, and inline assembly or compiler intrinsics.

Example scenarios:

• "You are experiencing sporadic latency spikes in a high-frequency sensor processing loop. How do you investigate if dynamic memory allocation is the cause, and how would you refactor the code to eliminate heap allocation during runtime?"
• "Implement a custom, thread-safe queue in C++ that supports non-blocking push and pop operations for a producer-consumer thread model."

Robotics Math, Localization, and Planning

For autonomy, perception, and planning roles, you must demonstrate the ability to convert mathematical concepts into robust software algorithms.

Be ready to go over:

• State Estimation & Filtering – Kalman Filters, Extended Kalman Filters (EKF), Bayesian probability, and sensor fusion algorithms.
• Geometry & Kinematics – Coordinate frame transformations, homogeneous transformation matrices, quaternions, and spatial representations.
• Path Planning & Control – Search algorithms (A*, Dijkstra), trajectory generation, vehicle kinematic models (bicycle model), and control loops (PID, MPC).
• Advanced concepts (less common) – Non-linear optimization, factor graphs, SLAM (Simultaneous Localization and Mapping), and machine learning models for perception.

Example scenarios:

• "Given a series of noisy range and bearing measurements from a radar sensor, walk through how you would initialize and update a Kalman filter state vector to track a lead vehicle's position and velocity."
• "Write a function to transform a 3D point cloud from the LIDAR sensor coordinate frame to the vehicle's ego coordinate frame given a translation vector and rotation quaternion."

System Design and Architecture

This area evaluates your capacity to build clean, maintainable, and highly performant software systems that run on physical hardware or scale in the cloud.

Be ready to go over:

• Modular Software Design – Interface segregation, dependency injection, and decoupling hardware interfaces from core autonomy logic.
• Data Pipelines & Middleware – Pub/sub architectures, shared memory communication, serialization protocols (Protobuf, FlatBuffers), and handling network latency.
• Diagnostics & Fault Tolerance – Designing fail-safe states, monitoring system health, logging under CPU/storage constraints, and error propagation.
• Advanced concepts (less common) – Designing for ISO 26262 (Functional Safety) compliance, SOTIF (Safety of the Intended Functionality), and hardware-in-the-loop (HIL) testing architectures.

Example scenarios:

• "Design the software architecture for an on-vehicle safety monitor that runs independently of the main autonomy stack. It must ingest vehicle speed and obstacle distance, and command an emergency brake if a collision is imminent and the main stack fails to respond."
• "How would you design a distributed logging system for a fleet of autonomous trucks that selectively uploads critical safety events over cellular connections while saving full raw sensor logs to physical SSDs for manual retrieval?"

Behavioral, Managerial, and Safety Culture

Your technical skills must be matched by professional maturity and an alignment with the safety-centric mission of Torc Robotics.

Be ready to go over:

• Safety-First Engineering – How you validate your code, your approach to code reviews, and how you handle tight deadlines without compromising software quality.
• Collaboration & Conflict Resolution – Navigating cross-functional disagreements (e.g., between software engineers and vehicle safety drivers) and aligning on technical directions.
• Handling Ambiguity – Delivering results when hardware specifications change or when working with unreleased, prototype systems.
• Advanced concepts (less common) – Leading post-mortem analyses of software failures, mentoring junior engineers on safety standards, and advocating for engineering best practices.

Example scenarios:

• "Describe a situation where you felt pressured to release a software feature or bug fix before you felt it was fully tested. How did you handle the situation, and what did you communicate to stakeholders?"
• "Walk me through a complex technical project you led. How did you manage the architectural trade-offs, and how did you ensure the final system was highly reliable and maintainable?"