Embedded AI Software Intern: Generative AI & RAG

Nissan Motor Co.; Barcelona; On-site; EUR 6,700 - 13,000; Full time

Benefits offered by this job

Paid internship

Job summary

Nissan Technical Centre Europe in Barcelona, Spain, offers an AI Internship for Embedded Software Development. The program focuses on exploring Generative AI technologies to enhance software development in embedded systems.

You will collaborate with engineers to develop AI-guided workflows, investigate Retrieval-Augmented Generation (RAG) and AI Agents, and document findings to inform future AI deployment across engineering processes.

Qualifications

• Enrolled in Bachelor's or Master's degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science or related disciplines.
• Interest in Generative AI Large Language Models (LLMs), RAG architectures, AI Agents, and Software Development.
• Proficiency in Python or similar programming languages.
• Strong analytical and problem-solving skills.
• Fluent English.

Responsibilities

• Contribute to the development of an AI-guided solution for Embedded Software Development based on current engineering processes.
• Investigate and apply Retrieval-Augmented Generation (RAG) technologies to facilitate access to relevant technical information and engineering documentation.
• Explore AI Agent technologies to support software developers during design and development activities.
• Help define AI-based workflows for Model-Based Development (MBD) software components.
• Collaborate with the engineering team to identify opportunities for Generative AI deployment within existing processes.

Job description

Nissan Technical Centre Europe in Barcelona, Spain, offers an AI Internship for Embedded Software Development. The program focuses on exploring Generative AI technologies to enhance software development in embedded systems.

You will collaborate with engineers to develop AI-guided workflows, investigate Retrieval-Augmented Generation (RAG) and AI Agents, and document findings to inform future AI deployment across engineering processes.