Senior Applied Scientist — AI Tooling & GenAI

Amazon Web Services (AWS); Austin (TX); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Employee assistance program

Job summary

Amazon Web Services, Inc. is seeking a Senior Applied Scientist to drive high-impact ML solutions for Proserve and Frontier AI, delivering models and tools that scale across sales and delivery teams.

You will own ambiguous problems, set technical direction, and mentor others while communicating complex insights clearly to executives and non-technical audiences. The role emphasizes production deployment of ML products, collaboration with customers across AWS Sales, and leadership in advancing the

Qualifications

• PhD, or Master's degree and 6+ years of building ML models for business applications.
• Experience with SQL and Python scripting.
• Experience presenting complex technical information to executives and non-technical leaders.
• Experience managing and deploying ML products.

Responsibilities

• Own the full lifecycle of complex science problems from framing to deployment.
• Set technical direction on ambiguous problems and design decisions.
• Partner with Sales & Delivery to translate business questions into science.
• Raise the scientific bar through reviews, mentorship, and guidance.
• Communicate methods, trade-offs, and results to technical and non-technical audiences.
• Use Python, PySpark, and SQL for data analysis and model development.

Skills

Python

SQL

Communication

ML deployment

Education

PhD or MS + 6+ years ML experience

Job description

Amazon Web Services, Inc. is seeking a Senior Applied Scientist to drive high-impact ML solutions for Proserve and Frontier AI, delivering models and tools that scale across sales and delivery teams.

You will own ambiguous problems, set technical direction, and mentor others while communicating complex insights clearly to executives and non-technical audiences. The role emphasizes production deployment of ML products, collaboration with customers across AWS Sales, and leadership in advancing the