Edge Deployment Engineer - (Embedded Ai) - Hybrid

Edge Deployment Engineer - (Embedded AI) - Hybrid A fantastic opportunity for a driven Edge Deployment Engineer to join a leading Quantum AI company, where you will work alongside world?leading experts in quantum computing and AI, developing solutions that deliver real?world impact for global clients.Fixed Term Contract until the end of June ** , with hybrid working from sites in Zaragoza or Barcelona.Required QualificationsBachelor’s degree or higher in Computer Science, Electrical Engineering, Physics, or related field; or equivalent industry experience3-5 years of hands?on experience in embedded systems, firmware development, or systems programmingDemonstrated experience optimizing machine learning models for deployment on constrained devicesStrong proficiency in Python, C, or C++; experience with system?level programming languages is essentialSolid understanding of quantization techniques and model compression strategies; experience with inference optimization frameworks (TensorRT, ONNX Runtime, LLM, vLLM, or equivalent)Familiarity with embedded architectures: ARM processors, mobile GPUs, and AI acceleratorsStrong fundamentals in computer architecture, memory management, and performance optimizationExperience with version control (Git), testing frameworks, and CI/CD pipelinesExcellent communication and collaboration skills in cross?functional teamsBy applying to this role you understand that we may collect your personal data and store and process it on our systems.For more information please see our Privacy Notice (/).#J-***-Ljbffr

Bachelor’s degree or higher in Computer Science, Electrical Engineering, Physics, or related field; or equivalent industry experience 3-5 years of hands?on experience in embedded systems, firmware development, or systems programming Demonstrated experience optimizing machine learning models for deployment on constrained devices Strong proficiency in Python, C, or C++; experience with system?level programming languages is essential Solid understanding of quantization techniques and model compression strategies; experience with inference optimization frameworks (TensorRT, ONNX Runtime, LLM, vLLM, or equivalent) Familiarity with embedded architectures: ARM processors, mobile GPUs, and AI accelerators Strong fundamentals in computer architecture, memory management, and performance optimization Experience with version control (Git), testing frameworks, and CI/CD pipelines Excellent communication and collaboration skills in cross?functional teams