Applied Scientist, SSG Science

Amazon Inc.; Asti; On-site; EUR 120,000 - 170,000; Full time

Job summary

Amazon Devices is an inventive research and development company designing devices like Kindle, Fire tablets, Fire TV, Echo and Astro. This role focuses on developing edge Gen AI techniques and co-design with ML hardware to deliver state-of-the-art consumer products.

We seek exceptional scientists to join our Applied Science team, optimize edge models, and publish open-source work at leading conferences such as NeurIPS and MLSys.

Qualifications

• Bachelor's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field.
• Experience programming in Java, C++, Python or related language.

Responsibilities

• Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms.
• Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques.
• Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine.
• Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics.
• Train custom Gen AI models that beat SOTA and paves path for developing production models.
• Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices.
• Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.

Skills

Java

C++

Python

Education

Bachelor's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field

Tools

Java

C++

Python

Job description

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History.

Key job responsibilities

• Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms
• Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques
• Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine
• Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics
• Train custom Gen AI models that beat SOTA and paves path for developing production models
• Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices
• Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.

Basic Qualifications

• Bachelor's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
• Experience programming in Java, C++, Python or related language

Preferred Qualifications

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals

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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.

Location: ES, Community of Madrid, Madrid