Position: Machine Learning Engineer
Company: IntelliBoard
Experience required: 3y
Category: Data Science
English level: intermediate
Published: 2020-09-01T00:00:00+03:00

Interested in Augmented Reality? Do you want to be part of a team that is changing the way the
world interacts with mobile devices? We are pioneering thenext wave of technology — reimagining
the way the world interacts withtechnology today. Our mission is to bring the digital and physical
worldstogether.
As a Computer Vision / Machine Learning Engineer you’ll work closely withother engineers on our
team to bring industry leading algorithms to a potentialmarket of billions of smartphone users.
We are looking for experienced,production-focused engineers who want to develop highly reliable
products in a collaborative fast-paced environment.

**Responsibilities**
1. Design, train, test, deploy, maintain and optimize ML-based computervision solutions.
2. Manage individual projects, systems and deliverables.
3. Minimum qualifications
4. MS or Ph.D. with a focus on computer vision or machine learning, or equivalent work
experience.
5. 2+ years of experience with computer vision or machine learningframeworks and libraries.
6. 2+ years of relevant research or professional experience in software development.
7. Research or professional coding experience in C/C++.
8. Preferred qualifications
9. Hands on experience with deep learning engines, e.g. TensorFlow, Caffe,Torch, Theano
or similar.
10. Extensive experience with data visualization e.g. in Python, Matlab, or highgui/viz.
11. 1+ year of experience with modern CNN/RNN construction (ResNet,Inception, LSTM, etc.).
12. Demonstrated examples of end to end projects for real world, real timeapplications.
13. Projects in computational geometry, linear algebra, convex optimization,HMM/POMDP, etc.
14. Experience that combines both machine learning and computer vision.
15. Bonus points
16. Extensive experience with computer vision libraries like OpenCV.
17. Experience with sensor fusion (IMU+vision) for tracking and mappingapplications.
18. Experience porting ML or computer vision runtimes to GPU architectures.