Amazon.com Services LLC
Technology
AppliedScientist,AGICustomization
Neural analysis suggests this role is
optimal for Senior candidates.
“Applied Scientist, AGI Customization at Amazon.com Services LLC. Skills: AGI Customization, Large language models, Model customization, Applied research. Contribute novel customization techniques. Develop extended post-training”
Industry & Context.
Optimization
What They're Looking For.
Must Have
3+ years building models, PhD or Master's degree, 4+ years CS, CE, ML experience, Experience programming Java, C++, Python, Experience algorithms and data structures, Experience parsing, Experience numerical optimization, Experience data mining, Experience parallel and distributed computing, Experience high-performance computing, 1+ years building ML models, Master's degree or PhD, 2+ years applied research experience, Experience state-of-the-art deep learning models, Experience deep learning training, Experience deep learning optimization, Experience model pruning
Nice to Have
Experience using Unix/Linux, Experience professional software development, PhD computer science, machine learning, engineering, Experience Machine and Deep Learning toolkits, Analytical skills, Attention to detail, Effective communication abilities, Experience software development, Experience managing networks, Experience troubleshooting networks, Experience developing algorithms supervised fine-tuning, Experience implementing algorithms supervised fine-tuning, Experience developing models supervised fine-tuning, Experience implementing models supervised fine-tuning, Experience developing algorithms reinforcement learning, Experience implementing algorithms reinforcement learning, Experience developing models reinforcement learning, Experience implementing models reinforcement learning, Experience patents top-tier conferences, Experience publications top-tier conferences, Experience patents top-tier journals, Experience publications top-tier journals
What You'll Do.
Contribute novel customization techniques
Develop extended post-training
Develop continued pre-training
Develop advanced knowledge distillation
Design enterprise-ready tooling
Implement enterprise-ready tooling
Optimize model accuracy
Optimize model latency
Develop preference learning algorithms
Develop training curricula
Create evaluation frameworks
Assess model performance
Contribute Responsible AI toolkit
Create training datasets
Create evaluation datasets
Design secure access mechanisms
Implement secure access mechanisms
Communicate technical insights
How You'll Work.
Team & Collaboration
Cross-functional teams
Communication Scope
Technical documentation; Presentations
Full Job Description
The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist to support adoption and enable customization of Amazon Nova. The role focuses on developing state-of-the-art services and tools for model customization, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models. As an Applied Scientist, you will play a important role in developing advanced customization capabilities that enable enterprises to build highly performant application-specific models without the need for training models from scratch. Your work will directly impact how companies leverage Amazon Nova models for their specific use cases. Key job responsibilities - Contribute to the development of novel customization techniques including extended post-training, continued pre-training, and advanced knowledge distillation - Collaborate with cross-functional teams to design and implement enterprise-ready tooling for various training techniques on Amazon SageMaker - Design and execute experiments to optimize model accuracy, latency, and cost across different customization approaches (SFT, DPO, PPO) - Develop and enhance preference learning algorithms and training curricula for customer-specific applications - Create robust evaluation frameworks for assessing model performance across different domains and use cases - Contribute to the development of the Responsible AI toolkit, including creating training and evaluation datasets for model alignment - Design and implement secure access mechanisms for early model checkpoints and weights - Communicate technical insights and results to both technical and non-technical stakeholders through presentations and documentation Basic Qualifications: - 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience in patents or publications at top-tier peer-re
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