Computer Vision Engineer

Computer vision engineers apply computer vision and machine learning research to solve real-world

problems. Their work uses large sums of data and statistics in order to complete complex tasks and

supervised learning as part of computer vision tasks. Their work uses large sums of data and statistics in

order to complete complex tasks and supervised learning as part of computer vision tasks. Influences top

management internally & externally (industry) to accept new ideas. Creates and conceptualizes solutions

to Artivatic in specific discipline.

Objective of the position:

The purpose of computer vision is to program a computer to understand a scene or features in an image.

Typical goals of computer vision include: The detection, segmentation, localization, and recognition of

certain objects in images (e.g., human faces)

Role and Responsibilities:

-Developing novel algorithms and modelling techniques to advance the state of the art in Document and

Text Extraction

-Image recognition, Object Identification, and Visual Recognition

-Working closely with R&D and Machine Learning engineers implementing algorithms that power user

and developer-facing products

-Be responsible for measuring and optimizing the quality of your algorithms

Mandatory traits/ skills:

-Excellent skills in developing Python in the Linux environment.

-Programming skills with multi-threaded GPUs.

-Experience in applying machine learning and computer vision principles to real-world data and working

in Scanned and Documented Images

-Good knowledge of Computer Science, math, and statistics fundamentals (algorithms and data

structures, meshing, sampling theory, linear algebra, etc.)

-Knowledge of data science technologies such as Python, Pandas, Scipy, Numpy, matplotlib, etc.

-Broad Computer Vision knowledge - Construction, Feature Detection, Segmentation, Classification;

Machine/Deep Learning - Algorithm Evaluation, Preparation, Analysis, Modeling, and Execution.

-Familiarity with Open CV, Dlib, Yolo, Capsule Network or similar and Open Source AR platforms and

products

-Have profound knowledge of Seq2Seq, temporal Classification, Opencv, etc.

-Should have logical knowledge for generating the real-time dataset.

-Added advantage if you have worked in Unstructured Documents

-Strong problem-solving and logical skills.

-A go-getter kind of attitude with a willingness to learn new technologies

-Well-versed in software design paradigms and good development practices

Qualifications

 Bachelors or Master's degree in Computer Science, Computer vision, or related field with

specialization in Image Processing or machine learning.

 3-8 Years of Industry experience in Computer Vision

 Research experience in Deep Learning models for Image processing or OCR-related field is preferred

 Publication record in Deep Learning models for Computer Vision conferences/journals is a plus