Remote QA Engineer (AI/ML Focus)
bout Special Projects Engineering LLC
Special Projects Engineering is a small, elite team based in Seattle tackling complex, high-impact problems using advanced AI and automation. We work across domains like autonomous systems, predictive infrastructure, synthetic biology, and next-gen defense tech. When something hasn’t been done before, we don’t shy away — we build it.
What You’ll Do
As a QA Engineer focused on ML/AI systems, your mission is to ensure the reliability, accuracy, and stability of intelligent systems that operate in messy, real-world environments. You’ll design robust testing frameworks and evaluation pipelines to validate everything from perception models to full-stack ML deployments.
Responsibilities:
• Develop and maintain automated test suites for machine learning pipelines and AI-enabled systems
• Create testing strategies for models handling visual, audio, sensor, and textual data
• Validate data inputs, model outputs, performance benchmarks, and edge-case behavior
• Build tools for continuous integration and regression testing across ML components
• Work with ML engineers to define evaluation metrics and acceptable thresholds
• Help ensure models are safe, stable, and robust before deployment
• Identify gaps in test coverage and build test plans that scale with the codebase
What We’re Looking For
• 3+ years in software QA, test automation, or related role
• Hands-on experience testing ML models or AI systems in production environments
• Strong Python skills; bonus if you’ve worked with PyTorch, TensorFlow, or JAX
• Familiarity with ML lifecycle and model validation techniques
• Experience with CI/CD pipelines, test frameworks, and debugging tools
• Detail-oriented mindset with strong instincts for edge cases and failure modes
• Bonus: background in data validation, simulation environments, or robotics
Why Join Us
• Remote first company
• Competitive salary and equity
• Flexible hours and remote-friendly culture
• Full health, dental, and vision insurance
• High-end GPU hardware and compute resources
• Work on real-world AI systems with a high-caliber team
• Fast-moving environment where your work directly impacts production
If you care about building AI that actually works, works well, and works safely — we’d love to talk.
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