At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
Were 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.
Youll own the architecture and implementation of systems that validate software, hardware, and AI model performance across diverse environments and edge cases. Youll 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. Youre 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 equivalent
10+ years of experience in software engineering, validation, or system testing roles
Strong background in building test or validation frameworks for complex, multi-component systems
Proficiency in Python or similar scripting languages; familiarity with C++ or embedded environments a plus
Experience validating AI/ML systems, including dataset curation, ground truth comparison, and edge case detection
Understanding of cloud infrastructure (e.g., AWS, GCP) and data pipelines
Experience working with hardware-in-the-loop or field-deployed systems is a strong plus
Comfortable working independently and owning cross-functional efforts from design through execution
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