SDE – Amazon Robotics

Amazon.com

Do you want to have a worldwide impact in Robotics? The Vulcan Stow team (https://w.amazon.com/bin/view/Vulcan_Robotic_Stow/) at Amazon Robotics builds high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. We invent and scale AI systems for robotics in fulfillment.

We are seeking software engineers to help with our initial robotic deployments. This includes building computer vision systems, ML and AI models, robotic control and motion planning, and process management. It also includes end-to-end ownership of decision explanation, fault detection, monitoring, A/B testing, large scale model training, simulation, hardware integration, and more. This work spans prototypes in the lab as well as wide-deployment systems. As a software engineer, you will help plan the roadmap, design ML systems, implement, test, and monitor services in our robotic fleet.

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

North Reading, MA, USA

Basic Qualifications

– 3+ years of non-internship professional software development experience
– 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
– Experience programming with at least one software programming language
– Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
– 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.

Preferred Qualifications

– 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
– Bachelor’s degree in computer science or equivalent
– Robotics experience along with experience with one of the following:
– * Production-level machine learning
– * Computer vision (e.g. a variety of neural network architectures using TensorFlow or MxNet, fusion with other sensors)
– * Hardware integration (e.g. hardware release cycles, heterogeneous hardware fleets)
– * Building and testing real-time or safety-critical systems

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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