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Internship - Machine Learning Research Engineer

Perplexity· Search
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Hybrid (Berlin)Full-timePosted 8mo ago

About the role

Internship program in Berlin focusing on advancing search quality through ML research and engineering work, with emphasis on large-scale deep learning, retrieval/ranking models, and RAG pipelines.

Responsibilities

  • Relentlessly push search quality forward — through models, data, tools, or any other leverage available.
  • 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 research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval.
  • Build and optimize RAG pipelines for grounding and answer generation.

Qualifications

  • Understanding of search and retrieval systems, including quality evaluation principles and metrics.
  • Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models.
  • Interested in representation learning, including contrastive learning, dense & sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation.
  • Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR).

Skills

Required:Search and retrieval systems understandingPyTorch and distributed trainingRepresentation learning and contrastive learning
Nice to have:Publication in AI/ML conferences
Last updated Sep 2, 2026. Interested? Apply on the company site.

About Perplexity

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