Eyenuk, Inc. is focused on quickly and accurately identifying patients suffering from potentially blinding diseases and preventing their vision. At Eyenuk, we are a bunch of highly motivated individuals, who dare to tread the challenging path, of taking machine learning, artificial intelligence algorithms and its supporting infrastructure to the next-level of scale and ease-of-use - to help, make the next big leap in medical science.
We are looking for individuals, who can be part of this team, with their undying enthusiasm, having the will to take challenges on the way, and are filled with ideas and energy to make this happen.
We are looking for Computer vision and Deep learning research engineers, with the below qualities...
Thrives on freedom with great responsibility, to develop a deep understanding of the domain
Has the right attitude to learn, work with a dynamic team & is open to ideas to make things happen
Conduct applied research in computer vision, deep neural networks, and medical image analysis.
Design and develop end-to-end solutions using modern machine learning and image analysis techniques.
Implement and optimize aforementioned algorithms in Python and/or C++, so as to deliver high-quality software for mobile, desktop, and cloud.
Work closely with clinicians (eg. ophthalmologists and retinal specialists) to define, clarify, and enhance the product and user experience.
Create intellectual property (patents), publish technical papers, present work at computer vision and medical (medicine/ophthalmology/diabetes) conferences.
Competitive salary plus healthy stock options in a growing company. High upside potential.
Join a diverse multi-disciplinary team; work closely with expert doctors and key opinion leaders, as well as with a solid technical team.
Work in a dynamic startup environment. No bureaucracy or limits on what you could do.
Contribute to and participate in the growth. Own ideas, turn them into products/features, watch customers love them, and get credit for all of this.
Opportunity to publish papers, attend conferences in varied fields, and to contribute to open source projects.
US-based candidates (H1-b or OPT ok)
PhD in Electrical Engineering, Computer Science, or related field.
Solid foundation in machine learning, computer vision, and image analysis. Experience with deep learning research and development.
Publication record in conferences such as CVPR, NIPS, ICML, ICIP, or similar is a big plus.
High proficiency in Python and/or C++; ability/willingness to learn other languages/tools.
Experience with one or more of open source tools such as Theano, PyTorch, Caffe, Tensorflow, OpenCV, and similar.
An understanding of computer science and software engineering fundamentals (data structures, algorithms, and software development process) and willingness to learn bits of human anatomy, clinical research concepts, and regulatory science, as needed.
Passion to turn ideas into working systems, with an eye for product design and engineering.