Senior Applied Scientist, Custom AI & Model Evaluation

Amazon Web Services (AWS); Denver (CO); In loco; USD 167.000 - 226.000; Tempo pieno

Descrizione del lavoro

Amazon Web Services, Inc. in Colorado, Denver seeks a Senior Applied Scientist to advance model customization from data curation to trusted evaluation and to produce reusable recipes and open-source accelerators for scalable, cost-effective customization on customer data.

You will spend half your time on direct customer engagements and half on building leverage through research assets and thought leadership.

Competenze

• PhD or Master's 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. Design the evaluation methodology behind every model-selection and customization decision.
• Lead customization engagements end to end. Drive work from data curation and synthetic data generation through fine-tuning and reinforcement learning.
• Invent where no textbook solution exists. Develop new techniques such as reward design for agentic tasks and efficient serving of small models.
• Turn engagement learnings into reusable assets. Build reference architectures, open-source accelerators, workshops, and papers.
• Advise field teams and customers. Act as the scientific advisor on trade-offs among prompting, retrieval, customization, and frontier models.
• Mentor and influence across teams. Mentor engineers and Solutions Architects in ML methodology.

Conoscenze

Java

Python

C++

ML model development

Formazione

PhD or Masters with 6+ years in applied research

Strumenti

scikit-learn

Spark MLlib

TensorFlow

MxNet

Descrizione del lavoro

Amazon Web Services, Inc. in Colorado, Denver seeks a Senior Applied Scientist to advance model customization from data curation to trusted evaluation and to produce reusable recipes and open-source accelerators for scalable, cost-effective customization on customer data.

You will spend half your time on direct customer engagements and half on building leverage through research assets and thought leadership.