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Description

Do you want to revolutionize machine learning on edge devices? Join our team developing best in class customer experience that enables AI models to run efficiently on resource-constrained hardware. Our work is transforming the way Amazon customers interact with our devices, creating novel experiences that push the boundaries of what's possible with AI.

About the role:

As an Applied Scientist on the Edge AI & ML team, you will be at the forefront of innovation, working on technology that directly impacts millions of Amazon customers. Our team is pioneering new approaches that help get AI experiences for customers on edge devices. You'll work on challenging problems at the intersection of deep learning, optimization, and systems.

By optimizing ML models for edge deployment, we're bringing advanced AI closer to our customers, enhancing privacy, reducing latency, and enabling new features that were previously impossible.

Key job responsibilities

As an Applied Scientist on the Edge AI ML team, you will:

- Conduct experiments to evaluate and benchmark model performance across various hardware platforms

- Collaborate with product teams to integrate our technology into Amazon devices and services

- Innovate on techniques to achieve state-of-the-art efficiency in AI model deployment

- Explore and adapt emerging ML architectures (e.g., transformers, neural architecture search) for edge computing

- Investigate hardware-aware ML techniques to tailor models for specific edge devices

About the team

The long term vision of the Tablet Edge AI team is to build a scalable hybrid edge-cloud orchestration framework with Agentic capabilities that enable context aware personalized experiences for customers. We envision a future where customer experiences transcend traditional app-centric models, evolving into natural, context-aware, and autonomous interactions.

Basic Qualifications

- 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

Preferred Qualifications

- 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.