Jobs / Germany / Perplexity

Perplexity

Internship - Machine Learning Research Engineer

Berlin Posted today

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Skills this job asks for

Machine learningDeep learningPyTorch

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Sponsorship verdict

No sponsorship evidence yet

No government record and no wording either way. Not a refusal: ask the recruiter.

  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • Can’t check pay against the visa rulesNo salary stated. Germany EU Blue Card needs at least €50,700 a year (shortage-occupation / recent-graduate: €45,934).
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Can’t check pay against the visa rules
No salary stated. Germany EU Blue Card needs at least €50,700 a year (shortage-occupation / recent-graduate: €45,934). Source: https://www.make-it-in-germany.com/en/visa-residence/types/eu-blue-card, rules effective 2026-01-01.

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Before you apply

Sponsorship unknown

No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.

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About the role

Internship Program Berlin Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office. 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). Find Jobs in Germany on Arbeitnow

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