Edge Development Engineer

Edge Deployment Engineer

A fantastic opportunity for a driven an Edge Development Engineer to join a leading Quantum AI company, who work on cutting-edge solutions that make AI faster, greener, and more accessible. You’ll be working alongside world-leading experts in quantum computing and AI, developing solutions that deliver real-world impact for global clients.

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.