We are seeking a Senior Computer Vision Test Engineer with a passion for quality, automation, and real-world impact. In this role, you will be responsible for designing, developing, and executing robust test strategies for cutting-edge perception systems.  At Metropolis, we build complex, distributed computer vision systems that span a wide range of platforms, from cameras and embedded edge devices to large-scale cloud infrastructures. These systems power, critical, real-time decisions across parking and new verticals. As a Senior Test Engineer, you will play a pivotal role in verifying that each component in this ecosystem functions correctly in isolation and as part of an integrated system. You’ll collaborate closely with engineers across software, hardware, and machine learning teams to define test coverage, develop test harnesses, and identify edge cases that impact performance in production. You will also help shape and improve our continuous integration pipelines and automated validation frameworks to support fast iteration and robust releases.

Responsibilities

• Design and implement test plans, test cases, and test automation frameworks for computer vision and machine learning pipelines.
• Validate the end-to-end performance of CV applications such as object detection, classification, and tracking under diverse scenarios and edge cases.
• Analyze system-level behavior and KPIs (latency, accuracy, robustness) using metrics-driven methodologies.
• Develop tools for test data generation, synthetic validation, and visualization of perception outputs.
• Collaborate with software, ML, hardware, and QA teams to ensure end-to-end system validation and release readiness.
• Investigate, root-cause, and document bugs and issues across the perception stack.
• Drive continuous improvement in test coverage, test automation, and system reliability.

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, or a related field.
• 5+ years of hands-on experience in software or system testing, with at least 2 years focused on computer vision (CV), perception, or machine learning systems in production.
• Proficiency in Python and C++ for test automation and strong experience with unit testing frameworks like GTest or PyTest.
• Experience designing and implementing end-to-end test strategies for distributed systems, including using version control like Git and CI/CD pipelines like Jenkins or GitHub Actions.
• Solid understanding of computer vision concepts such as detection, tracking, segmentation, and 2D/3D geometry.
• Demonstrated experience testing perception or computer vision systems in real-world or hardware-in-the-loop (HIL) environments.
• Familiarity with common ML frameworks like PyTorch and TensorFlow, and CV libraries like OpenCV.
• Strong debugging, profiling, and log analysis skills, especially in embedded or real-world deployment environments.
• Experience with containerization tools like Docker and simulation platforms such as CARLA or NVIDIA Drive Sim.
• Excellent communication skills with a strong ownership mindset and the ability to work independently.