Computer Vision Engineer
1 week ago
Primary Skills:
Computer Vision, Machine Learning, Artificial Intelligence, Python, Deep Learning
Degree:
B.Tech/B.E.
Required skills:
Bachelors or higher degree, in ECE, CS, or EEE disciplines with a strong programming knowledge.
Deep expertise in programming with Python, C/C++.
Good exposure to Py Torch/TensorFlow, OpenCV and related toolkits.
Some experience in image processing, machine learning.
Comfort with collaboration, open communication and reaching across functional borders.
Experience working in a research or academic environment.
Ability to clearly articulate design and implementation choices.
Ability to use a wide variety of open-source technologies and tools.
Comfort with frequent, incremental code testing and deployment.
Comfort with collaboration, open communication and reaching across functional borders.
Experience working in a research or academic environment.
Job Description:
iHub-Data is seeking a talented and experienced Machine Learning/Deep Learning Software Engineer to join our dynamic and innovative team. The ideal candidate should have a strong background in machine learning and deep learning, with hands-on experience in developing and implementing cutting-edge algorithms and models. As a Machine Learning/Deep Learning Software Engineer, you will play a crucial role in designing, developing, and optimizing our machine learning solutions to solve complex problems and drive innovation in our products. We are looking for a passionate engineer, who will help build, demonstrate on scale - practical applications in using images and video.
Key Responsibilities:
In this position, the person will be required to at least, but not limited to:
Scale up proof-of-concept (POC) applications using state-of-the-art implementations in machine learning and deep learning.
Evaluate and implement existing or create new or modifications ML/DL methods. Experience in building software prototypes of image processing, computer vision and machine learning applications is a must. Hands-on, experimental work in machine learning is an added advantage.
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