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 out-of-the-box 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 team's strategy and contribute to long-term 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 Master's 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, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit
https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
