Machine Learning Research Engineer (Member of Technical Staff)

• 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
• Relentlessly push search quality forward — through models, data, tools, or any other leverage available
• Architect and build core components of the search platform and model stack
• 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
• Conduct advanced research in representation learning, including contrastive learning, multilingual, and multimodal modeling for search and retrieval
• Deploy models — from boosting algorithms to LLMs — in a scalable and performant way
• Build and optimize RAG pipelines for grounding and answer generation
• Collaborate with Data, AI, Infrastructure, and Product teams to ensure fast and high-quality delivery

Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areasStrong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large modelsProven track record with large-scale search or recommender systemsExpertise in representation learning, including contrastive learning and embedding space alignment for multilingual and multimodal applicationsDeep understanding of search and retrieval systems, including quality evaluation principles and metricsSelf-driven, with a strong sense of ownership and executionStrong publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR)