Member of Technical Staff (Machine Learning Research Engineer)

About the role

Perplexity is looking for an experienced Machine Learning Research Engineer to advance next‑generation search technologies, focusing on retrieval and ranking.

Key responsibilities

• Push search quality forward through models, data, tools, and other levers.
• Architect and build core components of the search platform and model stack.
• Design, train, and optimise large‑scale deep learning models using PyTorch and distributed training frameworks (e.g., PyTorch Distributed, DeepSpeed, FSDP).
• Conduct advanced research in representation learning, including contrastive, multilingual, and multimodal modelling for search.
• Deploy models—from boosting algorithms to LLMs—in a scalable, performant way.
• Build and optimise RAG pipelines for grounding and answer generation.
• Collaborate with Data, AI, Infrastructure, and Product teams to ensure fast, high‑quality delivery.

Required profile

• Deep understanding of search and retrieval systems, quality evaluation principles and metrics.
• Proven track record with large‑scale search or recommender systems.
• Strong publication record in top AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, SIGIR).
• Self‑driven with a strong sense of ownership and execution.
• Minimum of 3 years (preferably 5+) working on search, recommender systems, or closely related research areas.

Required skills

• PyTorch
• Distributed training techniques (PyTorch Distributed, DeepSpeed, FSDP)
• Hardware acceleration for large models
• Representation learning, contrastive learning, multilingual and multimodal modelling
• Large‑scale deep learning model design and optimisation
• LLM integration and deployment
• RAG pipeline development
• Boosting algorithms