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. Apply tot his job