Member of Technical Staff Machine Learning Research Engineer

Perplexity is an AI-powered answer engine that provides real-time, cited answers and research capabilities.

San Francisco, United States
About Perplexity

Private AI company founded in 2022. Its products combine conversational search and research with cited web sources; it also offers developer-facing Search, Agent, Router, and Embeddings APIs.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will advance search quality by building core search-platform and model-stack components. You will design, train, optimize, and deploy large-scale retrieval and ranking models; research representation learning; build RAG pipelines; and work with Data, AI, Infrastructure, and Product teams to deliver high-quality systems quickly.

Requirements

  • Deep understanding of search and retrieval systems, including quality evaluation principles and metrics
  • Proven track record with large-scale search or recommender systems
  • Proficiency with PyTorch, distributed training techniques, and large-model performance optimization
  • Expertise in representation learning, contrastive learning, and embedding-space alignment for multilingual and multimodal applications
  • Strong publication record in AI or ML conferences or workshops
  • Minimum of 3 years working on search, recommender systems, or closely related research areas

Responsibilities

  • Improve search quality through models, data, tools, and other approaches
  • Architect and build core search-platform and model-stack components
  • Design, train, and optimize large-scale deep-learning models for retrieval and ranking
  • Conduct research in representation learning, contrastive learning, multilingual modeling, and multimodal modeling
  • Deploy scalable, performant models ranging from boosting algorithms to LLMs
  • Build and optimize RAG pipelines for grounding and answer generation
  • Collaborate with Data, AI, Infrastructure, and Product teams to deliver quickly and with high quality