Virtual Test Engineer

Primary

Purpose:

The Virtual Testing team at Motional is responsible for validating the safety, functionality, and performance of our self-driving technology through rigorous, system-level testing. As a Test Engineer, you will play a hands‑on role in the end‑to‑end verification of AV features—spanning perception, planning, and control—using virtual modalities including simulation and Hardware-in-the-Loop (HIL).

You will contribute to test strategy, scenario creation, and infrastructure development. Collaborating with cross‑functional teams, you will help translate engineering requirements into comprehensive test plans, automated test cases, and measurable outcomes. Your efforts will support iterative development, fault injection analysis, and safety‑critical system evaluation, ensuring that every release meets the highest standards for quality and reliability.

• Contribute to a high‑performing team that prioritizes quality, continuous improvement, and robust validation throughout the development lifecycle.
• Design and execute test campaigns for self‑driving vehicle features, with a focus on perception, planning, and control systems, across both virtual and on‑vehicle environments.
• Develop and maintain detailed test plans, cases, and automation scripts using Python and Bash/Shell.
• Leverage Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and scenario‑based simulation platforms—such as Applied Intuition—for feature validation and regression testing.
• Create synthetic and resimulation scenarios to support iterative development, root‑cause analysis, and large‑scale release validation.
• Analyze logs and data to assess system behavior and conduct root‑cause investigations, collaborating cross‑functionally with perception, planning, hardware, and safety teams.
• Participate in recursive testing cycles, contributing to QA and release efforts throughout the AV software development lifecycle (SDLC).
• Document test procedures, results, and technical findings using tools like Confluence, Jira, and Git Lab, ensuring traceability and alignment with quality standards.
• Ensure testing practices comply with industry standards such as ISO
  26262, ISO
  21448 (SOTIF), and ISO
  9001.
• Continuously adapt test strategies to evolving AV stacks and fast‑paced development cycles.
• Support flexible testing schedules, including late meetings as required by fleet operations or global team collaboration.
• Collaborate across multiple projects and disciplines, gaining exposure to diverse engineering challenges and contributing to system‑level integration milestones.
• Enhance tools and processes for integrated testing workflows, including system integration, simulation‑based validation, and track‑based testing.
• Show initiative and thrive in an innovative, fast‑paced environment that encourages collaboration and creative problem solving.
• Contribute to the development of new tools, processes, and solutions that shape the future of safe, autonomous mobility.
• Additional duties as assigned.
• Willingness to travel domestically as needed.

• Education:
  
  Bachelor’s degree or higher in Engineering, Robotics, ECE, Computer Science, or a relevant technical field.

• Experience:
  
  2+ years in software QA, systems testing, or mechatronic system validation, preferably within ADAS or autonomous systems.

• Technical
  
  Skills:

  • Proficiency in Linux and programming/scripting languages such as Python, C++, or Bash/Shell.
  • Experience writing and developing comprehensive test cases and test plans.

• Domain Expertise (One or more of the following):

  • Virtual/Simulation:
    Proficiency with AV simulation platforms (e.g., Applied Intuition, IPG Carmaker, NVIDIA DRIVE Sim).
  • HIL/Hardware:
    Hands‑on experience with Hardware-in-the-Loop (HIL) environments and automotive communication protocols (CAN, LIN, Ethernet).
  • Field/Track:
    Experience with track‑based testing and mechatronic system integration.

• Problem Solving:
  Demonstrated ability to troubleshoot, debug, and think logically to remove bias from problem evaluation.

• Adaptability:
  Ability to operate effectively amid ambiguity and interpret evolving system requirements in a fast‑paced environment.

• Understanding of industry standards…