Computer Vision Engineer

Tap is a transformative technology that provides the missing link in how we will interact with the coming wave of AI Smart Glasses and Mixed Reality headsets. The Tap device is a one-handed, wearable keyboard and input device that creates commands when you tap your fingers on any surface, allowing you to quickly, easily and accurately interface with any bluetooth enabled host.

Tap Systems, Inc. is a US corporation with R&D headquarters in Modiin, Israel. 

Visit www.tapwithus.com to learn more.

We are looking for a talented applied researcher to build the core computer vision algorithms and ML models for the next generation Tap wearable. This product is a stand alone multi-modal data processor, backed with Computer Vision algorithms packed in a small footprint with aggressive power constraints. 

If you are passionate about deep learning for computer vision, have strong attraction to data analysis and are not afraid of challenges - we are looking for you. 

You will work with our multidisciplinary team of hardware, software and design engineers to help create the next generation of Tap.

Responsibilities:

• Play a hands-on, critical role in the definition and development of the company's core technologies.
• Collaborate with the data team to help define, expand, and maintain our data assets.
• Explore, evaluate and optimize SOTA architectures to fit our product needs.
• Maintain tools and pipelines to support the ML and data lifecycle.
• Develop proficiency around model optimization techniques for embedded inference and edge compute.

Required Skills and Experience:

• At least 3 years of hands-on experience in deep learning for Computer Vision deep learning models design.
• Theoretical and practical understanding of ML fundamentals and SOTA Deep Learning approaches.
• Open minded, creative and proactive, with a ‘can do’ attitude
• Experience with Tensorflow/Pytorch
• Experience with Edge ML inference frameworks - Advantage
• Must be able to collaborate with a multidisciplinary engineering team.