<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <strong>Internship Program Berlin<br/><br/></strong>Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office.<br/><br/><strong>Responsibilities<br/><br/></strong><ul><li>Relentlessly push search quality forward — through models, data, tools, or any other leverage available.</li><li>Train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models.</li><li>Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval.</li><li>Build and optimize RAG pipelines for grounding and answer generation.<br/><br/></li></ul><strong>Qualifications<br/><br/></strong><ul><li>Understanding of search and retrieval systems, including quality evaluation principles and metrics.</li><li>Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models.</li><li>Interested in representation learning, including contrastive learning, dense &amp; sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation.</li><li>Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR).<br/><br/></li></ul> </div>