What You’ll Do?
You will own full responsibility for designing, implementing and maintaining
the product ML models. Our Deep Learning models run on low compute edge
devices, inferring on diverse data sources such as live vision, sound, and
more. Collaborate with cross-functional teams such as research, product,
hardware, and electronics. 

Roles and responsibilities
- Analyze problems to decide on sampling & learning strategy
- Design ML (usually DL) models for audio/visual/other sensors data
- Analyze model's performance to Iteratively improve them
- Work with ML-ops for continuous performance monitoring, models
update, and inference on low-compute edge machines
- Improve data acquiring process, e.g reduce noise using classic
computer vision 
Required education and experience
- At least 3 years of experience with Deep Learning in diverse data
source advantage for working with audio data.
- At Least 2 years Experience in Classic Computer Vision.
- Good familiarity with python and its ML & CV libraries
(TensorFlow/PyTorch, sklearn,openCV, skimage)
Qualifications
- A creative, out-of-the-box thinker. 
- Initiative, efficient, and lean-thinker. 
- Responsible and well organized. 
- Self-learner.
- Ability to excel under pressure and adapt to dynamic constraints. 
- Work effectively as a team member, and across the organization
- Ability to troubleshoot and analyze complex problems.