Internship - Machine Learning Research Engineer

<p style="min-height:1.5em"><strong>Internship Program Berlin</strong></p><p style="min-height:1.5em">Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office.</p><p style="min-height:1.5em"><strong>Responsibilities</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Relentlessly push search quality forward — through models, data, tools, or any other leverage available.</p></li><li><p style="min-height:1.5em">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.</p></li><li><p style="min-height:1.5em">Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval.</p></li><li><p style="min-height:1.5em">Build and optimize RAG pipelines for grounding and answer generation.</p></li></ul><p style="min-height:1.5em"><strong>Qualifications</strong></p><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Understanding of search and retrieval systems, including quality evaluation principles and metrics.</p></li><li><p style="min-height:1.5em">Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models.</p></li><li><p style="min-height:1.5em">Interested in representation learning, including contrastive learning, dense &amp; sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation.</p></li><li><p style="min-height:1.5em">Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR).</p></li></ul><p>Find <a href="https://www.arbeitnow.com">Jobs in Germany</a> on Arbeitnow</a>