Machine Learning Engineer, AWS Identity Analytics Platform

Amazon • Seattle, WA

5d

About The Position

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.

Requirements

• 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

Nice To Haves

• 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

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.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level