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Nanonets

Sr. Deep Learning Engineer

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Description

Responsibilities:

  • Build and deploy state-of-the-art, generalizable deep learning architectures for complex real-world problems.
  • Develop models that can convert unstructured data into structured information without extensive hand-tuned features.
  • Research, experiment and incorporate the latest advancements in Deep Learning, LLMs and VLMs.
  • Build production-grade Deep Learning systems that operate at scale.
  • Solve challenging problems across Computer Vision, NLP and Multimodal AI.
  • Develop advanced solutions for document understanding, information extraction and intelligent automation.


Requirements:

  • 5-8 years of experience in Deep Learning.
  • Strong fundamentals in Deep Learning architectures, LLMs and VLMs.
  • Strong expertise in at least one area such as: Computer Vision, NLP, Multimodal AI, Generative AI.
  • Experience building and deploying production-grade Deep Learning systems at scale.
  • Familiarity with major LLMs such as GPT, LLaMA, Claude and their applications.
  • Strong software engineering practices including Git/version control, CI/CD and code quality.
  • Ability to quickly learn, experiment and apply new research and technologies.

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