Deep Learning Vision Engineer
Geomagical Labs is an early-stage startup in the San Francisco Bay Area, applying novel computer vision technologies to an exciting, consumer application to be used by millions of people.
We have an opening for an deep learning vision engineer with strong academic foundations and substantial hands-on experience with image-based artificial neural networks, to join our core startup team of computer vision scientists and engineers.
As a Deep Learning Vision Engineer, you will design, implement and tune state-of-the-art hybrid machine vision architectures for broad vision problems, such as image-based classification, segmentation, regression, object detection & information fusion. You must be familiar with state of art ANN/CNN architectures and training techniques for practical vision problems, and eager to solve technical problems that you may have not encountered before.
This position requires strong theoretical foundations, excellent engineering skills, and sound scientific method. Candidates must also be adventurous and enthusiastic about an early startup experience!
- Strong C.S. & machine learning foundations from a competitive university/laboratory (Ph.D. preferred).
- Fluency in TensorFlow, PyTorch, Caffe 2 strongly desired.
- Strong programming background in C++ and Python, in Linux environments.
- Strong applied math skills in linear algebra and linear & non-linear optimization.
- Hands-on experience with 2D/3D computer vision (e.g. stereo matching & flow, image/video segmentation, object instance detection, computational photography & rendering, scene perception).
- Substantial industrial work experience applying deep learning to various computer vision problems is a big plus.
- Familiarity with 3D computer graphics is a plus
- Excited about seed-stage startups; entrepreneurial, comfortable with risk & uncertainty.
- U.S. work visa required.
- Rare opportunity to join an early tech startup adventure when it is less than ten people, led by founders who've taken two startup teams through IPO.
- Substantial stock equity packages, of the sort only available to early startup employees.
- Opportunity to publish novel and influential research, participate in scientific conferences, and collaborate with partners in academia.
- We are located in Mountain View, California, near bicycle trails and Caltrain.