Senior Applied Scientist - AI Customization & Data Architecture

Amazon.com Inc.; Denver (CO); In loco; USD 167.000 - 226.000; Tempo pieno

Vantaggi offerti da questo lavoro

Health insurance

401(k) matching

Paid time off

Parental leave

Descrizione del lavoro

Amazon Web Services (AWS) is seeking a Sr. Applied Scientist in Applied AI & Data Architecture to drive customization and evaluation of foundation models on customer data.

You will design rigorous evaluation methods, develop reference implementations, and publish reusable assets across regions to scale adoption. The role balances direct customer engagements with building scalable science assets, open-source projects, and thought leadership.

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 application.

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, distillation, and reinforcement learning.
• Invent new techniques and packaging them as reusable code for field use.
• Turn engagement learnings into reusable assets, reference architectures, and open-source work.
• Advise field teams and customers on trade-offs among prompting, retrieval, and frontier models.
• Mentor engineers and Solutions Architects in ML methodology.

Conoscenze

Java

C++

Python

Formazione

PhD, or Master’s degree with 6+ years of applied research

Strumenti

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Descrizione del lavoro

Amazon Web Services (AWS) is seeking a Sr. Applied Scientist in Applied AI & Data Architecture to drive customization and evaluation of foundation models on customer data.

You will design rigorous evaluation methods, develop reference implementations, and publish reusable assets across regions to scale adoption. The role balances direct customer engagements with building scalable science assets, open-source projects, and thought leadership.