Amazon Device software team is looking for an exceptional, motivated software engineer to implement computer vision system on the Edge. This is an ambitious undertaking to create a new device category from ground up and is replete with technical challenges. You will take an exciting and challenging role on a team and work with world-class engineers, business leaders, and other talented engineering teams while you design, architect, and code for our computer vision platform for the edge.
You will be part of a passionate team whose missions is to push the frontier of computer vision and machine learning technology into the smart home application area. This is a great opportunity for you to innovate in this space by developing software at the edge and in the cloud, and integrating them into consumer services to enable a premium customer experience.
In this role, you will design and implement complex sensor network system/algorithm in computer vision and related disciplines. You will translate business and functional requirements into working code. You will build large-scale infra to facilitate using a large amount of data to train and test computer vision systems.
- 3+ years of programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
- 2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- 4+ years of professional software development experience
- 2+ years of relevant experience in building production-scale system/algorithm in one of the following domains: computer Vision, deep learning, or machine learning.
- Experience with embedded devices.
- Masters or PhD in Computer Science or related field focus on computer vision research and deep learning.
- Experience investigating, designing, prototyping, and productizing new and innovative computer vision system solutions
- Experience in building and productizing Machine Learning models.
- Experience working with deep learning frameworks like TensorFlow, PyTouch, MxNet, ONNX, and Caffe.
- Knowledge of GPU programming (CUDA or OpenCL) on GPU accelerator architectures.
- Experience with camera bring-up and ISP pipeline configuration.
- Ability to juggle multiple priorities and make things happen quickly.
- Exceptional writing and verbal communications skills.