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Hayden AI

Principal QA Engineer

Reposted 12 Days Ago
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In-Office
San Francisco, CA
Expert/Leader
In-Office
San Francisco, CA
Expert/Leader
Design and implement a scalable validation infrastructure for real-world vehicle behavior detection systems, ensuring software, hardware, and AI model performance.
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About Us

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.

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 system—spanning custom cameras, edge AI hardware, cloud pipelines, and user-facing tools—performs 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 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

Top Skills

AWS
C++
GCP
Python

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