Edge Deployment Engineer (Fixed-term contract) at MULTIVERSE COMPUTING

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

12 Feb, 26

Salary

0.0

Posted On

14 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Embedded Systems, Firmware Development, Systems Programming, Machine Learning Optimization, Python, C, C++, Quantization Techniques, Model Compression, Inference Optimization, Embedded Architectures, Computer Architecture, Memory Management, Performance Optimization, Version Control, CI/CD Pipelines

Industry

Software Development

Description

We are looking to fill this role immediately and are reviewing applications daily. Expect a fast, transparent process with quick feedback. Why join us? We are a European deep-tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide — compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50–80%. Joining us means working on cutting-edge solutions that make AI faster, greener, and more accessible — and being part of a company often described as a “quantum-AI unicorn in the making.” We offer Competitive annual salary Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion. Relocation package (if applicable). Fixed-term contract ending inn June 2026. Hybrid role and flexible working hours. Be part of a fast-scaling Series B company at the forefront of deep tech. Equal pay guaranteed. International exposure in a multicultural, cutting-edge environment. 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 Preferred Qualifications Master’s degree in Computer Science, Electrical Engineering, or related field Hands-on experience with large language model inference and deployment Experience optimizing neural networks using mixed-precision computation or dynamic quantization Familiarity with edge computing frameworks such as NVIDIA’s Triton Inference Server or similar platforms Background in mobile or IoT development Knowledge of hardware acceleration techniques and specialized instruction sets (SIMD, NPU-specific optimizations) Contributions to open-source embedded AI or ML optimization projects Experience with real-time operating systems or embedded Linux environments About Multiverse Computing Founded in 2019, we are a well-funded, fast-growing deep-tech company with a team of 180+ employees worldwide. Recognized by CB Insights (2023 & 2025) as one of the Top 100 most promising AI companies globally, we are also the largest quantum software company in the EU. Our flagship products address critical industry needs: CompactifAI → a groundbreaking compression tool for foundational AI models, reducing their size by up to 95% while maintaining accuracy, enabling portability across devices from cloud to mobile and beyond. Singularity → a quantum and quantum-inspired optimization platform used by blue-chip companies in finance, energy, and manufacturing to solve complex challenges with immediate performance gains. You’ll be working alongside world-leading experts in quantum computing and AI, developing solutions that deliver real-world impact for global clients. We are committed to an inclusive, ethics-driven culture that values sustainability, diversity, and collaboration — a place where passionate people can grow and thrive. Come and join us! As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.

Responsibilities

The Edge Deployment Engineer will work on optimizing machine learning models for deployment on constrained devices and contribute to the development of cutting-edge AI solutions. This role involves collaboration with cross-functional teams to enhance the efficiency and accessibility of AI technologies.