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Description

Ring is looking for an Embedded Software Engineer to join the team, to support the computer vision machine learning infrastructure that provides smart and rich notifications to Ring customers worldwide.

We're committed to making home and neighborhood security accessible and effective for everyone – while working hard to bring communities together. Since its founding in 2013, Ring has been on a mission to make neighborhoods safer. From the video doorbell to the DIY Ring Alarm system, Ring’s smart home security product line offers users affordable whole-home and neighborhood security.

Key job responsibilities

You will be part of a cross-functional development team, responsible for implementing and improving computer vision algorithms that deliver high-performance detection and classification at exceptionally low power consumption. As a member of the team, you will collaborate in the deployment of software to millions of existing Ring devices, and improve customer experience with cutting-edge SOCs in new products.

A day in the life

You will work closely with applied science teams working on computer vision algorithms to help implement on device and deliver exciting features for customers. You will be responsible for coding, testing, maintaining, and working with product teams and QA to ensure features meet desired functionality and quality.

We are open to hiring candidates to work out of one of the following locations:

Cambridge, GBR

Basic Qualifications

• Experience in embedded development in C/C+- Knowledge of ARM CPUs

• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

• Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems

• Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems

• Experience in professional, non-internship software development

• Bachelor's degree in computer science or equivalent

• Experience with the deployment and/or development of Machine Learning and Deep Learning models on Edge

• Proficient communication and interpersonal skills

• Proficient data analysis and troubleshooting skills

Preferred Qualifications

• Experience implementing computer vision machine learning algorithms on edge

• Knowledge of Unix/Linux environments and embedded Linux

• Experience with software testing (unit, integration, and system testing)

• Experience with Python and tool creation

• Experience working with distributed systems or applications

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