Senior Applied Scientist, AI Customization & Evaluation

Amazon Web Services (AWS); Seattle (WA); In loco; USD 167.000 - 226.000; Tempo pieno

Descrizione del lavoro

Amazon Web Services, Inc. is seeking a Senior Applied Scientist to guide enterprises in customizing foundation models, evaluate results, and deploy tailored solutions on customer data.

You will balance parameter-efficient fine-tuning, distillation, and reinforcement fine-tuning while building reusable recipes and accelerators. The role splits roughly 50/50 between direct customer engagements and creating scalable, reusable assets, with collaboration across AI service teams and field engineers to

Competenze

• PhD or Master’s degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• 4+ years of building machine learning models for business applications.

Mansioni

• Own the evaluation methodology for model selection and customization, scoring quality, cost, latency and safety.
• Lead customization engagements end to end, from data curation to fine-tuning and reinforcement learning.
• Invent new techniques and reusable code for evaluation and deployment of models.
• Turn engagement learnings into reusable assets, reference architectures and open-source accelerators.
• Advise field teams and customers on trade-offs among prompting, retrieval and frontier models.
• Mentor engineers and Solutions Architects in ML methodology.

Conoscenze

Programming in Java/C++/Python

Formazione

PhD, or Master's degree and 6+ years of applied research experience

Descrizione del lavoro

Amazon Web Services, Inc. is seeking a Senior Applied Scientist to guide enterprises in customizing foundation models, evaluate results, and deploy tailored solutions on customer data.

You will balance parameter-efficient fine-tuning, distillation, and reinforcement fine-tuning while building reusable recipes and accelerators. The role splits roughly 50/50 between direct customer engagements and creating scalable, reusable assets, with collaboration across AI service teams and field engineers to