Generative AI Intern

Job Description:

We are looking for a passionate and highly motivated Research Engineer to join our team and contribute to the advancement of Language Model capabilities. As part of our team, you will play an integral role in researching and implementing cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and other state-of-the-art methods to enhance the performance of our models. If you are excited about working on innovative technologies, fine-tuning models, and building scalable AI systems, this is the perfect opportunity for you!

Key Responsibilities:

• Engage in research and implementation of Retrieval-Augmented Generation (RAG) and other advanced techniques to enhance Language model capabilities.

• Participate in data preparation for fine-tuning processes.

• Assist in setting up and optimizing the pipeline for fine-tuning,  Quantization.

• Participate in the training of small transformer models, ensuring performance and efficiency.

• Contribute to the development of an internal orchestration framework for LLM.

• Collaborate with senior engineers to integrate LLM SW Components into the existing system architecture.

• Support the deployment and monitoring of models in production environments.

• Document processes, workflows, and findings to ensure knowledge sharing and reproducibility.

Qualifications:

• Strong Python skills.

• Experience with Data Wrangling and Preprocessing.

• Familiarity with LangChain, LlamaIndex, and VectorDB.

• Good understanding of transformer architecture, embeddings, and tokenizers.

• Experience with machine learning frameworks like TensorFlow or PyTorch.

• Understanding of LLMs, fine-tuning techniques, and RAG methodologies.

• Proficiency in version control systems (e.g., Git) and software development best practices.

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

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At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.