What The Job Involves
We're looking for a hands-on Principal Quality & Validation Engineer to design and build the validation infrastructure for our real-world vehicle behavior detection system. This role is critical to ensuring our end-to-end systemspanning custom cameras, edge AI hardware, cloud pipelines, and user-facing toolsperforms accurately and reliably at scale.
You'll own the architecture and implementation of systems that validate software, hardware, and AI model performance across diverse environments and edge cases. You'll work across embedded software, machine learning, data pipelines, cloud infrastructure, and web platforms.
The ideal candidate has deep experience building validation frameworks for complex systems, involving ML / CV systems. You're comfortable both designing systems and diving into implementation. You care about product quality, take ownership, and thrive in fast-moving environments.
Responsibilities :
- Design and implement a scalable validation infrastructure for system-level testing across hardware, AI, and software components
- Develop tools and frameworks to evaluate accuracy, reliability, and edge case behavior in production-like environments
- Collaborate with engineering, product, and operations teams to define test strategies aligned with product use cases
- Analyze system performance and identify failure modes across the full pipeline : from sensor input to user output
- Automate validation workflows to accelerate development cycles and reduce regressions
- Serve as a technical resource for quality across the engineering organization
Required Qualifications :
B.S. in an engineering discipline or equivalent10+ years of experience in software engineering, validation, or system testing rolesStrong background in building test or validation frameworks for complex, multi-component systemsProficiency in Python or similar scripting languages; familiarity with C++ or embedded environments a plusExperience validating AI / ML systems, including dataset curation, ground truth comparison, and edge case detectionUnderstanding of cloud infrastructure (e.g., AWS, GCP) and data pipelinesExperience working with hardware-in-the-loop or field-deployed systems is a strong plusComfortable working independently and owning cross-functional efforts from design through execution