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European Tech Recruit • Barcelona, Catalonia, Spain
Role & seniority: AI QA Engineer; mid-level (minimum ~2+ years in QA with ML focus)
Stack/tools: Python; API testing; cloud-based ML platforms; automation and performance testing; ML lifecycles, LLMs (RAG, chatbots, data pipelines)
Ensure system integrity and high-tier performance of AI-driven products
Define acceptance criteria with product/engineering/clients; formalize success metrics
Design unified QA processes, build bespoke ML/test suites, and validate complex API/model outputs
Master’s degree in CS/Data Science/Software Engineering or related field
≥2 years QA experience with automation and performance in ML environments
Expertise in AI testing challenges: bias detection, model reproducibility, output validation
Hands-on Python, API testing, and cloud ML platforms
Strong English; French or Spanish a plus
Experience with RAG, LLMs, and data pipelines; QA process architecture
Experience advocating QA best practices and documentation improvements
Location & work type: Barcelona, Spain; hybrid work (3 days on-site) with commuting distance in Europe; full-time role
We are looking for AI QA Engineer to join an exciting European DeepTech start-up in Barcelona. They can offer hybrid working (3 days on-site) within a commutable distance.
They’re a fast-growing AI & quantum computing company that develops cutting-edge software that boosts performance & efficiency.
System Integrity: Guarantee the resilience and high-tier performance of all AI-driven products delivered to our partners.
Requirements Engineering: Partner with product leads, engineers, and clients to formalize rigorous acceptance criteria and success metrics.
Stress Testing: Assess system behavior under diverse conditions to ensure data integrity, low latency, and seamless scalability.
Process Architecture: Design and implement unified quality control protocols and reporting standards across the organization.
Specialized Validation: Build and manage bespoke test suites specifically engineered for ML lifecycles and LLM architectures (including RAG, chatbots, and data pipelines).
Framework Development: Execute a hybrid of manual and automated testing strategies to validate complex API integrations and model outputs.
Quality Advocacy: Drive the evolution of QA best practices, focusing on the continuous improvement of documentation and pipeline validation.
Final Certification: Act as the definitive technical authority for quality, certifying that all deliverables achieve functional excellence.
Master’s degree in Computer Science, Data Science, Software Engineering, or a relevant technical field At least 2 years of experience in QA, with a dedicated focus on automation and performance within machine learning environments Deep understanding of AI-specific testing challenges, such as bias detection, model reproducibility, and output validation Hands-on experience with Python, API testing, and cloud-based ML platforms Exceptional English skills; fluency in French or Spanish is an advantage
Feel free to also refer someone you may know who could be good for the role. If they are successfully placed, we offer a great referral scheme!
Key words – Quality Engineering / AI Testing / Machine Learning / Python / Test Automation
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