As a Senior Applied Scientist you will take on complex customer problems distill customer requirements and then deliver solutions that either leverage existing academic and industrial research or utilize your own outofthebox but pragmatic thinking. In addition to coming up with novel solutions and prototypes you will directly contribute to implementation. You will help guide and mentor our team of applied scientists and engineers. A successful candidate has excellent technical depth scientific vision project management skills great communication skills and a drive to achieve results in a partnership focused team environment.
Key job responsibilities Architect design and implement Machine Learning (ML) models for Computer Vision systems
Optimize deploy and support at scale ML models on the edge. Influence the teams strategy and contribute to longterm vision and roadmap.
Work with stakeholders across science and operations teams to iterate on design and implementation.
Maintain high standards by participating in reviews designing for fault tolerance and operational excellence and creating mechanisms for continuous improvement.
Prototype and test concepts or features both through simulation and emulators and with live robotic equipment
Work directly with customers and partners to test prototypes and incorporate feedback
Mentor other engineer team members.
About the team Data Center Automation team is responsible for building the systems that automate and orchestrate the physical work processes that occur inside all of AWS global datacenters. Our talented team of datacenter engineers depend on our systems to perform their work safely securely efficiently and free of defects resulting in the backbone of products the compute infrastructure.
3 years of building machine learning models for business application experience PhD or Masters degree and 6 years of applied research experience Experience programming in Java C Python or related language Experience with neural deep learning methods and machine learning
Experience with modeling tools such as R scikitlearn Spark MLLib MxNet Tensorflow numpy scipy etc. Experience with large scale distributed systems such as Hadoop Spark etc.
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