Information Retrieval Algorithm Engineer

Huawei Amsterdam Research Center is at the forefront of artificial intelligence and machine learning innovation. We are dedicated to developing cutting-edge technologies that revolutionize how people interact with information and enhance productivity across various sectors. Our team of experts is committed to pushing the boundaries of what's possible in AI, and we are looking for talented individuals to join us on this exciting journey.

Position Overview:
We are seeking a highly skilled and motivated Research Engineer to join our team, focusing on information retrieval and generative models. In this role, you will be responsible for developing, implementing, and optimizing models to enhance the accuracy and efficiency of information retrieval and the user experience of using generative models. In particular, we are interested in the multimodality scenario where the inputs are not necessarily text only. You will work closely with a team of researchers, data scientists, and engineers to create innovative solutions that leverage large-scale datasets and advanced machine learning techniques.

Key Responsibilities:
Design, implement, and optimize information retrieval models and establish a strong retrieval-augmented generation (RAG) system.

Enhance the user experience by improving LLM's reasoning capabilities and reducing the hallucinations
Conduct research on state-of-the-art methods in natural language processing (NLP), machine learning (ML), and information retrieval (IR).
Develop algorithms and techniques to improve the performance and scalability of RAG systems.
Collaborate with cross-functional teams to integrate RAG solutions into existing products and services.
Perform data collection, pre-processing, and analysis to support research and development activities.
Evaluate and benchmark the performance of RAG models using large-scale datasets.
Stay up-to-date with the latest advancements in AI, NLP, ML, and IR.

Qualifications:
Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on NLP, ML, or IR.
Strong programming skills in Python and familiarity with machine learning frameworks such as PyTorch.
Solid understanding of deep learning architectures, including transformers, BERT, GPT, etc.
Proven track record of research excellence, demonstrated through publications in relevant conferences and journals.
Ability to work independently and as part of a collaborative team.
Excellent problem-solving skills and attention to detail.
Strong communication skills, both written and verbal.

Preferred Qualifications:
Knowledge and hands-on experience on automatic speech recognition (ASR) is a big plus.
Experience with retrieval-based models and techniques, including vector space models, BM25, or neural retrieval methods.
Familiarity with knowledge bases, information extraction, and question answering systems.
Background in software development and engineering best practices.