Member of Technical Staff (Machine Learning Research Engineer)

<p style="min-height:1.5em">Perplexity is seeking an experienced Machine Learning Research Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.</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">Architect and build core components of the search platform and model stack</p></li><li><p style="min-height:1.5em">Design, 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 advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrieval</p></li><li><p style="min-height:1.5em">Deploy models — from boosting algorithms to LLMs — in a scalable and performant way</p></li><li><p style="min-height:1.5em">Build and optimize RAG pipelines for grounding and answer generation</p></li><li><p style="min-height:1.5em">Collaborate with Data, AI, Infrastructure, and Product teams to ensure fast and high-quality delivery</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">Deep understanding of search and retrieval systems, including quality evaluation principles and metrics</p></li><li><p style="min-height:1.5em">Proven track record with large-scale search or recommender systems</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">Expertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applications</p></li><li><p style="min-height:1.5em">Strong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR)</p></li><li><p style="min-height:1.5em">Self-driven, with a strong sense of ownership and execution</p></li><li><p style="min-height:1.5em">Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas</p></li></ul><p>Find <a href="https://www.arbeitnow.com">Jobs in Germany</a> on Arbeitnow</a>