Senior Machine Learning Engineer, AWS Identity Analytics Platform

AWS Identity Analytics is re-imagining how identity data is understood, acted on, and used to protect customers at scale. We build an AI-driven analytics platform that turns 50+ PB of raw logs and metrics into proactive, actionable insights for AWS Identity leadership and core service teams — including IAM and STS. AWS teams across the organization also rely on our platform for impact analysis related to AWS Auth.

Are you excited by the prospect of analyzing and modeling petabyte-scale data and building state-of-the-art ML algorithms to solve real-world security and operational problems? Do you want to work on a platform that directly shapes how AWS Identity services evolve — and influences decisions that affect hundreds of millions of customers globally? Do you thrive in ambiguous, fast-paced environments where your ML based work drives measurable business outcomes?

This role offers unprecedented breadth in ML applications: from time-series anomaly detection and causal policy evaluation to LLM-powered analytics agents and optimization systems. You will work alongside talented engineers and product leaders in a culture that prizes initiatives, rigor, and bias for action. You'll have access to AWS-scale compute resources including access to bleeding edge AWS and Nvidia silicon in massive high-performance clusters. What makes this role unique is the combination of ML depth with direct, observable impact: your models will surface insights that Identity leadership acts on, and the AI based solutions will change how service teams interact with data every day.



Key job responsibilities
Design, develop, and deploy end-to-end ML solutions — including anomaly detection, time-series forecasting, classification, and optimization models — that turn Identity logs, policies, and metrics into proactive, actionable insights.

Build and operate LLM-powered agents that serve as intelligent interfaces to Identity data, enabling service teams to query, explore, and act on insights conversationally.

Engineer features from petabyte-scale datasets using AWS services (Glue, Athena, EMR) and deploy models to production environments (SageMaker, ECS, EKS).

Partner with AWS Identity leadership, Product managers, IAM, STS, and other service teams to define success metrics, design experiments, validate models, and translate findings into decisions.

Stay at the forefront of innovation by applying state-of-the-art techniques in ML, deep learning, and GenAI to Identity Analytics challenges, fostering rapid experimentation and continuous learning.

Communicate complex technical concepts clearly to audiences of varying technical sophistication, including senior leadership.

Mentor junior engineers and contribute to the team's long-term technical direction.

BASIC QUALIFICATIONS

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in machine learning, data mining, information retrieval, statistics or natural language processing

PREFERRED QUALIFICATIONS

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers.