Data Science
Machine Learning (ML)About Us :
Docsumo is Document AI software that helps enterprises capture data and analyze customer documents. We convert documents such as invoices, ID cards, and bank statements into actionable data. We are work with clients such as PayU, Arbor and Hitachi and backed by Sequoia, Barclays, Techstars, and Better Capital.
As a Senior Machine Learning you will be working directly with the CTO to develop end to end API products for the US market in the information extraction domain.
Responsibilities :
- You will be designing and building systems that help Docsumo process visual data i.e. as PDF & images of documents.
- You'll work in our Machine Intelligence team, a close-knit group of scientists and engineers who incubate new capabilities from whiteboard sketches all the way to finished apps.
- You will get to learn the ins and outs of building core capabilities & API products that can scale globally.
- Should have hands-on experience applying advanced statistical learning techniques to different types of data.
- Should be able to design, build and work with RESTful Web Services in JSON and XML formats. (Flask preferred)
- Should follow Agile principles and processes including (but not limited to) standup meetings, sprints and retrospectives.
Skills / Requirements :
- Minimum 3+ years experience working in machine learning, text processing, data science, information retrieval, deep learning, natural language processing, text mining, regression, classification, etc.
- Must have a full-time degree in Computer Science or similar (Statistics/Mathematics)
- Working with OpenCV, TensorFlow and Keras
- Working with Python: Numpy, Scikit-learn, Matplotlib, Panda
- Familiarity with Version Control tools such as Git
- Theoretical and practical knowledge of SQL / NoSQL databases with hands-on experience in at least one database system.
- Must be self-motivated, flexible, collaborative, with an eagerness to learn
Subodh Popalwar
Software Engineer, Memorres
About Docsumo
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Software Engineer, Memorres