Technical Management Jobs in Mumbai - IIT Bombay
Technical Management
Job Description
1. Understanding the requirements in detail and eliciting them from the involved stakeholders
2. Leading the machine learning team and guiding them in the challenges that they are facing
3. Collaborating with the backend development team and ensuring the requirements are implemented correctly and the project is headed on the right track
4. Organizing meetings with all the required stakeholders and discussing the requirements, issues, challenges, updates, and progress relevant to the project
5. Overseeing that the development and testing are done as per industry standards and a proper pipeline is followed to ensure smooth operations of the project
6. Deploying the system on private servers and then handling the server operations
7. Managing the team and overseeing the tasks done by them
8. Recruiting skilled team members as per the needs of the project
9. Coordinating with industry experts and taking technical inputs from them in the challenges faced during the project
10. Maintaining the product backlog and software documentation
Note: This is a technical management role where you would be required to lead a backend team working on C++/Python and also to lead the ML team. Technical guidance will be provided by industry experts or professors but the candidate needs to execute the work with the team and manage it efficiently.
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 1st Feb'21 and 8th Mar'21
3. are available for duration of 6 months
4. have relevant skills and interests
We are working on detecting the layout of the OCRed text, preserving it, and reflecting it to automate the annotation task. Optical character recognition (OCR) is the process of converting document images into an editable electronic format. OCR in Indian languages is quite challenging due to richness in inflections. Using open-source and commercial OCR systems, we have observed the word error rates (WER) of around 20-50% on printed documents in four different Indic languages. Moreover, developing a highly accurate OCR system with an accuracy as high as 90% is not useful unless aided by the mechanism to identify errors. So, we started with the problem of developing 'OpenOCRCorrect', an end-to-end framework for error detection and corrections in Indic-OCR. Our models outperform state-of-the-art results in 'Error Detection in Indic-OCR' for six Indic languages with varied inflections and we have solved the out of vocabulary problem for âError Correction in Indic-OCRâ in our ICDAR-2017 conference paper. We further improve the results with the help of sub-word embeddings in our ICDAR-2019 conference paper.
There is an immediate demand to keep the softcopy of the Indian preserved texts. Currently, we are targeting Sanskrit. Although the OCR tools available online do a decent job on English texts, they are not optimized for Indic languages. Thus, we developed an in-house OCR model for the same. The model can detect text with the maximum level of accuracy and can draw bounding boxes on each line of the text. Further, in the digitization process of such texts, the second step would be spelling correction and formatting of the text detected by the OCR models.
Certificate: Will be provided at the end of the Internship
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