Edge ai engineer/staff software engineer
Pubblicato il 01-08-2026 - Qualcomm in Italia
What you'll work on As part of a talented engineering team, you will: Design and develop containerized AI model runners and execution environments for high‐performance Linux embedded platforms. Build Python‐based libraries and frameworks to simplify the integration of complex AI inference engines for the Arduino community. Optimize ML model deployment pipelines, ensuring efficient resource utilization on constrained hardware. Collaborate with Software Architects to define technical solutions using the latest software development technologies and infrastructure. Ensure consistency, efficiency and high quality of the Arduino codebase through automated testing coverage and code reviews. Contribute creative solutions to enhance Arduino applications and tools within a cross‐functional team. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field – 4+ years of Software Engineering or related experience. Master's degree in Engineering, Information Systems, Computer Science,
or related field – 3+ years of Software Engineering or related experience. Ph D in Engineering, Information Systems, Computer Science, or related field – 2+ years of Software Engineering or related experience. 2+ years of work experience with programming languages such as C, C++, Java, Python, etc. What you'll bring BS/MS in Computer Science, Artificial Intelligence, or other technical related fields. 5+ years of software development work experience. Strong experience in Python development, specifically for creating production‐grade libraries and tooling. Deep knowledge of containerization (and Docker) within the context of Linux systems. Familiarity with AI inference engines (Tensor Flow Lite, ONNX Runtime, ...), local LLM frameworks (Ollama, llama.cpp, ...) and model optimization techniques (quantization, pruning, fine tuning, ...). High motivation and interest in pushing the boundaries of current technologies. Deep understanding of performance