Applied Scientist, Personalization & Recommender Systems

Amazon Science; New York (NY); On-site; USD 157,000 - 213,000; Full time

Benefits offered by this job

RSUs

Health insurance

Paid time off

Parental leave

Job summary

Amazon Science in New York seeks an Applied Scientist to push state-of-the-art machine learning and recommendations, leveraging large datasets and massive compute resources. You will design, implement, and launch AI features for personalization on the retail platform.

You will conduct offline/online experiments, collaborate with engineers and product partners globally, and publish findings at top conferences.

Qualifications

• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field.
• Experience programming in Java, C++, Python or related language.
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse.
• Experience publishing at top-tier conferences or journals.

Responsibilities

• Using Amazon’s large-scale computing resources, ask research questions about customer behavior, build state-of-the-art models to optimize the shopping experience, and run these models directly on the retail website.
• Develop AI solutions for Recommendation systems using Deep learning, LLMs, Reinforcement Learning, distillation, and Optimization methods.
• Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end.
• Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses.
• Effectively communicate technical and non-technical ideas with teammates and stakeholders.
• Publish your research findings in top conferences and journals.

Skills

Java

C++

Python

Machine Learning

Education

Master's degree in CS or quantitative field

Tools

SQL

Oracle

Data Warehouse

Job description

Amazon Science in New York seeks an Applied Scientist to push state-of-the-art machine learning and recommendations, leveraging large datasets and massive compute resources. You will design, implement, and launch AI features for personalization on the retail platform.

You will conduct offline/online experiments, collaborate with engineers and product partners globally, and publish findings at top conferences.