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Internship - Machine Learning Research Engineer

Perplexity

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1,088 open learning roles across 268 companies are on ApplySarthi right now, most of them in Bengaluru (63), Hyderabad (24), Delhi NCR (14).

What learning roles keep asking for: Machine learning (48%), Python (36%), LLMs (22%), PyTorch (22%), Deep learning (16%), AWS (13%), Generative AI (13%) — counted across their open postings here.

Deep learning jobs · PyTorch jobs · RAG jobs

Perplexity has 123 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

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Interviews for learning roles keep coming back to Machine learning, Python, LLMs, PyTorch. Practise those questions before you sit with Perplexity.

Questions you are likely to be asked

  1. Why do you want to join Perplexity?
  2. What is your experience with PyTorch? Tell me one thing you learned the hard way.
  3. What would you check first if a model's accuracy dropped after going live?
  4. When would you not use machine learning for a problem?
  5. Walk me through a model you built, from the data to how it was used.

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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).

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Listed on ashby · posted 2026-09-02. ApplySarthi collects openings and links to application pages; the role is advertised by Perplexity, not by us.