Information Retrieval Algorithm Engineer

A leading Amsterdam-based research center is at the forefront of artificial intelligence and machine learning innovation. They are dedicated to developing cutting-edge technologies that revolutionize how people interact with information and enhance productivity across various sectors. Their team of experts is committed to pushing the boundaries of what is possible in AI, and they are looking for talented individuals to join them on this exciting journey.

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.

Requirements

• 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.

Bonus Requirements

• 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.