Search Machine Learning Research Engineer

Perplexity is seeking an experienced Senior Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retrieval and ranking.ResponsibilitiesRelentlessly push search quality forward — through models, data, tools, or any other leverage availableArchitect and build core components of the search platform and model stackDesign, 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 modelsConduct advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrievalDeploy models — from boosting algorithms to LLMs — in a scalable and performant wayBuild and optimize RAG pipelines for grounding and answer generationCollaborate with Data, AI, Infrastructure, and Product teams to ensure fast and high-quality deliveryQualificationsDeep understanding of search and retrieval systems, including quality evaluation principles and metricsProven track record with large-scale search or recommender systemsStrong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large modelsExpertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applicationsStrong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR)Self-driven, with a strong sense of ownership and executionMinimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas