- Deployed large scale multi-modal architectures that can understand both text and images really well.
- Built an auto-ML platform that can automatically select best architecture, fine-tuning method based on type and amount of data.
- Best in the world models to process documents like invoices, receipts, passports, driving licenses, etc
- Hierarchical information extraction from documents. Robust modeling for the tree-like structure of sections inside sections in documents.
- Extracting complex tables – wrapped around tables, multiple fields in a single column, cells spanning multiple columns, tables in warped images, etc.
- Enabling few-shots learning by SOTA finetuning techniques.
Candidate should have experience working on Deep Learning with an engineering degree from a top tier institute
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