Applied Scientist AGI - Neural Efficiency Science
Applied Scientist AGI - Neural Efficiency Science
Posted on :
12-04-2025
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1 Vacancy
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Monthly Salary
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Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
12-04-2025
Job Description
Join the Amazon AGI team to revolutionize the future of AI by developing breakthrough technologies that dramatically improve the efficiency of large language and foundation models. Work at the frontier of AI research designing novel approaches for model compression efficient architectures long context extension and training optimization that will shape the next generation of AI systems.
Were seeking exceptional Applied Scientists to join our team dedicated to solving one of AIs most critical challenges: making foundation models more efficient through lower latency and higher throughput. Youll work on research and new technology development while collaborating with worldclass researchers and engineers.
Pioneer new approaches to foundation models
Publish and present research at toptier conferences and journals
Work with stateoftheart LLMs and multimodal foundation models
Access to substantial computational resources for research
Collaborate across AGI teams to implement solutions at scale
Key job responsibilities
Research and develop novel techniques for efficient runtime inference (low latency high throughput)
Design and evaluate efficient foundation model architectures
Create new methods for improving training efficiency
Conduct experimental studies to validate efficiency improvements
Write highquality Python code to implement research ideas
Collaborate with team members to integrate solutions into production systems
Author technical documentation and research papers
Present findings to technical and nontechnical stakeholders
A day in the life
Your day might start with a team standup to discuss ongoing projects and brainstorm solutions to technical challenges. Youll spend time implementing and testing new efficiency optimization techniques in Python analyzing performance metrics and iterating on approaches. Youll collaborate with team members to review code and research results participate in technical discussions about architecture designs and engage with other AGI teams to understand their efficiency needs. You might end your day analyzing experimental results or writing up findings for a research paper. Throughout the week youll have opportunities to present your work to stakeholders and contribute to the teams research roadmap.
Our stakeholders include other AGI teams within Amazon and our work directly impacts the cost and performance of AI systems used across Amazons products and services. Youll be solving complex technical challenges that make advanced AI more accessible and efficient at scale.
About the team
The Neural Efficiency Science team was founded in 2024 to develop new technologies that improve the costtoperformance ratio of AGI foundation models. Amazon believes in customerobsessed research and as a large number of AI applications are getting built we see a need to invest in making the underlying foundation models serving these applications cheaper faster and more accurate at a given price point. Our team keeps up with all of the latest research and trends in what we call neural efficiency and publishes our own findings at top conferences such as ICML and NeurIPS while also making our technology available in production for internal and external customers.
3 years of building models for business application experience
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience programming in Java C Python or related language
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
Experience building machine learning models or developing algorithms for business application
Experience in patents or publications at toptier peerreviewed conferences or journals
Experience in professional software development
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race national origin gender gender identity sexual orientation protected veteran status disability age 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Were seeking exceptional Applied Scientists to join our team dedicated to solving one of AIs most critical challenges: making foundation models more efficient through lower latency and higher throughput. Youll work on research and new technology development while collaborating with worldclass researchers and engineers.
Pioneer new approaches to foundation models
Publish and present research at toptier conferences and journals
Work with stateoftheart LLMs and multimodal foundation models
Access to substantial computational resources for research
Collaborate across AGI teams to implement solutions at scale
Key job responsibilities
Research and develop novel techniques for efficient runtime inference (low latency high throughput)
Design and evaluate efficient foundation model architectures
Create new methods for improving training efficiency
Conduct experimental studies to validate efficiency improvements
Write highquality Python code to implement research ideas
Collaborate with team members to integrate solutions into production systems
Author technical documentation and research papers
Present findings to technical and nontechnical stakeholders
A day in the life
Your day might start with a team standup to discuss ongoing projects and brainstorm solutions to technical challenges. Youll spend time implementing and testing new efficiency optimization techniques in Python analyzing performance metrics and iterating on approaches. Youll collaborate with team members to review code and research results participate in technical discussions about architecture designs and engage with other AGI teams to understand their efficiency needs. You might end your day analyzing experimental results or writing up findings for a research paper. Throughout the week youll have opportunities to present your work to stakeholders and contribute to the teams research roadmap.
Our stakeholders include other AGI teams within Amazon and our work directly impacts the cost and performance of AI systems used across Amazons products and services. Youll be solving complex technical challenges that make advanced AI more accessible and efficient at scale.
About the team
The Neural Efficiency Science team was founded in 2024 to develop new technologies that improve the costtoperformance ratio of AGI foundation models. Amazon believes in customerobsessed research and as a large number of AI applications are getting built we see a need to invest in making the underlying foundation models serving these applications cheaper faster and more accurate at a given price point. Our team keeps up with all of the latest research and trends in what we call neural efficiency and publishes our own findings at top conferences such as ICML and NeurIPS while also making our technology available in production for internal and external customers.
3 years of building models for business application experience
PhD or Masters degree and 4 years of CS CE ML or related field experience
Experience programming in Java C Python or related language
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing
Experience in stateoftheart deep learning models architecture design and deep learning training and optimization and model pruning
Experience building machine learning models or developing algorithms for business application
Experience in patents or publications at toptier peerreviewed conferences or journals
Experience in professional software development
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race national origin gender gender identity sexual orientation protected veteran status disability age 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Employment Type
Full-Time
Key Skills
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