Applied Scientist II - Real-Time AI Learning Recommender

Amazon Inc.; Bellevue (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC in Bellevue, WA is seeking an Applied Scientist II for Central Learning Solutions Science. You will lead research on learning and development, design science-informed learning journeys, and develop real-time personalized recommendations for leadership and associates using GenAI-based chat assistants.

You will collaborate with a large team of experts to advance learning experience research, communicating insights clearly to both technical and non-technical audiences.

Qualifications

• 3+ years of building models for business applications.
• PhD or Master’s +4 years in CS/CE/ML or related field.
• Experience in patents or publications at top-tier conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel & distributed computing, HPC.

Responsibilities

• Apply science models to extract actionable information from learning feedback.
• Build recommender systems to generate personalized learning interventions for Ops employees.
• Leverage GenAI/LLM technology for scaling learning experience workflows.
• Design and implement metrics to evaluate AI models.
• Present analyses to technical and non-technical stakeholders and influence business partners.

Skills

Model building

Java

C++

Python

Algorithms & data structures

Data mining

Parallel & distributed computing

High-performance computing

Education

PhD or Master’s in CS/CE/ML with 4+ years

Tools

MxNet

TensorFlow

Job description

Amazon.com Services LLC in Bellevue, WA is seeking an Applied Scientist II for Central Learning Solutions Science. You will lead research on learning and development, design science-informed learning journeys, and develop real-time personalized recommendations for leadership and associates using GenAI-based chat assistants.

You will collaborate with a large team of experts to advance learning experience research, communicating insights clearly to both technical and non-technical audiences.