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🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
ExecutivePlacements.com • Boston, Massachusetts, United States
Role & seniority: QA Engineer (mid to senior level) focused on ML/AI systems
Stack/tools: Python; ML frameworks (PyTorch, TensorFlow, or JAX); ML pipelines; CI/CD; testing frameworks; data validation and debugging tools
Develop and maintain automated test suites for ML pipelines and AI-enabled systems
Create testing strategies for models handling visual, audio, sensor, and textual data; validate data inputs, model outputs, performance, and edge cases
Build tools for CI/regression testing across ML components; work with ML engineers to define evaluation metrics and thresholds; ensure models are safe, stable, and robust before deployment; identify coverage gaps and plan scalable tests
3+ years in software QA, test automation, or related role
Hands-on experience testing ML models or AI systems in production
Strong Python skills; familiarity with ML lifecycle and model validation techniques; experience with CI/CD and debugging tools
Detail-oriented with strong edge-case/ failure-mode instincts
Remote-first company; flexible hours; remote-friendly culture; Seattle-based elite team
Full health/dental/vision insurance; competitive salary and equity; access to high-end GPU hardware and compute resources
Special Projects Engineering LLC -
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 hasnt been done before, we dont shy away we build it.
What Youll 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. Youll 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 Were 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 youve 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 wed love to talk.