Edge Deployment Engineer - (Embedded AI) - Hybrid

European Tech Recruit; Zaragoza; Hybrid; EUR 50,000 - 70,000; Full time

Job summary

A leading Quantum AI company based in Spain is seeking an Edge Deployment Engineer to work in a hybrid environment. Candidates should possess a Bachelor's degree in a relevant field and 3–5 years of relevant experience, particularly in embedded systems and firmware development. The role involves optimizing machine learning models for deployment, utilizing Python, C, or C++. Excellent collaboration skills are essential, along with a strong grasp of computer architecture. The fixed-term contract extends until June 2026.

Qualifications

• 3–5 years of hands-on experience in embedded systems or firmware development.
• Experience optimizing machine learning models for constrained devices.
• Strong fundamentals in computer architecture and performance optimization.

Skills

Embedded systems

Firmware development

Machine learning model optimization

Python

C

C++

Version control (Git)

Cross-functional collaboration

Education

Bachelor's degree in Computer Science, Electrical Engineering, Physics, or related field

Tools

TensorRT

ONNX Runtime

Job description

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 2026, with hybrid working from sites in Zaragoza or Barcelona.

Required Qualifications

• 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

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