Applied Scientist II, Sheriff Team- Payroll tech
Core
Developing and maintaining ML and Generative AI applications for Payroll Operations and Amazon employees, including anomaly detection, intelligent ticket prioritization, virtual assistance, and automated policy extraction.
Role type
Senior Applied Scientist (ML & GenAI)
Builds
Production ML models and GenAI systems for payroll anomaly detection, ticket classification, virtual assistant (Penny), and policy-as-code extraction (PoCo).
Domain
Payroll technology, Large Language Models (LLMs), Generative AI
Deliverable
production ML models
Required skills
Novel ML and LLM-based methodology design, anomaly detection, sentiment analysis, ticket classification, automated policy extraction, high-performance computing, parallel and distributed computing, numerical optimization, algorithms and data structures, Java/C++/Python programming
Preferred skills
LLM fundamentals and optimization, deploying LLMs on AI acceleration hardware (GPUs/Neuron/TPU), data mining, information retrieval, statistics, natural language processing, relational analytic DBMS, Elastic-Search, Big Data EMR/EC2/Glue/Lambda, Unix/Linux
Technologies
LLMs, GenAI frameworks, Neuron, TPU, Elastic-Search, EMR, EC2, Glue, Lambda, Java, C++, Python
Responsibilities
Design novel ML approaches for anomaly detection and policy extraction, lead scientific strategy for global expansion of ticket prioritization systems, mentor scientists and engineers on AI-Driven Development Life Cycle, author peer-reviewed articles, integrate models into production systems serving global payroll operations.
Seniority
Senior, hands-on IC with research leadership
