


Responsibilities
- Build and mentor the computer vision team at TransPacks
- Drive to productionize algorithms (industrial level) developed through hard-core research
- Own the design, development, testing, deployment, and craftsmanship of the teamās infrastructure and systems capable of handling massive amounts of requests with high reliability and scalability
- Leverage the deep and broad technical expertise to mentor engineers and provide leadership on resolving complex technology issues
- Entrepreneurial and out-of-box thinking essential for a technology startup
- Guide the team for unit-test code for robustness, including edge cases, usability, and general reliability
Ā
Eligibility
- Tech in Computer Science and Engineering/Electronics/Electrical Engineering, with demonstrated interest in Image Processing/Computer vision (courses, projects etc) and 6-8 years of experience
- Tech in Computer Science and Engineering/Electronics/Electrical Engineering, with demonstrated interest in Image Processing/Computer vision (Thesis work) and 4-7 years of experience
- D in Computer Science and Engineering/Electronics/Electrical Engineering, with demonstrated interest in Image Processing/Computer vision (Ph. D. Dissertation) and inclination to working in Industry to provide innovative solutions to practical problems
Requirements
- In-depth understanding of image processing algorithms, pattern recognition methods, and rule-based classifiers
- Experience in feature extraction, object recognition and tracking, image registration, noise reduction, image calibration, and correction
- Ability to understand, optimize and debug imaging algorithms
- Understating and experience in openCV library
- Fundamental understanding of mathematical techniques involved in ML and DL schemas (Instance-based methods, Boosting methods, PGM, Neural Networks etc.)
- Thorough understanding of state-of-the-art DL concepts (Sequence modeling, Attention, Convolution etc.) along with knack to imagine new schemas that work for the given data.
- Understanding of engineering principles and a clear understanding of data structures and algorithms
- Experience in writing production level codes using either C++ or Java
- Experience with technologies/libraries such as python pandas, numpy, scipy
- Experience with tensorflow and scikit.

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