Applied Scientist, Internal Audit

Amazon; Baltimore (MD); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon seeks an Applied Scientist to accelerate Internal Audit’s Data Science & Risk Intelligence. You will build ML and generative AI products, automating audit workflows with agentic AI and retrieval-augmented generation.

You will deploy secure AWS ML solutions, mentor teammates, and steer production-ready research, balancing rigor with impact in a fast-paced environment.

Qualifications

• 3+ years of building models for business applications.
• PhD, or MS/BS with 4+ years CS/CE/ML experience.
• Experience programming in Java, C++, Python or related language.
• Experience with ML and LLM fundamentals, model lifecycle, and production systems.
• Experience architecting solutions on AWS or cloud-based tech.

Responsibilities

• Partner with audit teams, product managers, engineers to define ML/AI products end-to-end.
• Design and own agentic AI systems, including multi-agent workflows and tools.
• Apply statistical analysis and ML on large datasets to provide insights.
• Architect secure, scalable AWS ML/generative AI solutions from design to production.
• Own production and experimentation infra, deployment pipelines, observability.
• Drive applied research and disseminate findings through talks and publications.

Skills

ML fundamentals

Python

Java/C++

SQL

LLMs

AWS

Education

PhD

MS/BS CS/ML

Tools

AWS Bedrock

SageMaker

AgentCore

LangGraph

Strands

Job description

Job ID: 10535487 | Amazon.com Services LLC

Are you passionate about data, enjoy solving complex analytical problems, leveraging industry leading agentic AI technologies to derive insight at scale - all in a challenging, fast-paced environment? We are seeking an Applied Scientist to accelerate the growth of Amazon Internal Audit’s Data Science & Risk Intelligence initiatives. The team builds ML and AI solutions that expand self-service data utilization by audit teams, utilizing the right methods to derive deeper patterns, and surface insights to gain holistic perspectives while amplifying potential risk mitigation.

Key job responsibilities

• Partner with audit teams, product managers, engineers, and scientists to define and deliver machine learning and generative AI products that carry significant ambiguity, scale, and complexity, owning problems end-to-end, from framing through measurable impact.
• Design, build, and own agentic AI systems, including multi-agent workflows, retrieval-augmented generation, and tool-using agents, that automate and augment audit work, and set the standard for how the team evaluates them through rigorous LLM-as-judge and human-aligned evaluation.
• Apply statistical analysis and classical machine learning using SQL and scripting languages like Python/R over large datasets to develop insights and recommendations that strengthen internal audit.
• Architect secure, scalable solutions on AWS machine learning and generative AI services (e.g., Bedrock, AgentCore, SageMaker), owning the full lifecycle from design through production deployment, monitoring, and iterative improvement.
• Own and evolve the team's production and experimentation infrastructure, including deployment pipelines, observability and tracing, and evaluation harnesses.
• Drive applied research by identifying and pursuing emerging techniques, and disseminate findings through internal and external publications, talks, and journal clubs.
• Raise the technical bar across the team, including mentor junior scientists and engineers, review designs and code, and help shape the product and technical roadmap.

A day in the life

As an Applied Scientist, you will own ambiguous, high-impact problems and help shape the technical roadmap that connects risk to Amazon. You will drive AI products that make audit work more effective and efficient, increasingly centered on LLM and agentic systems. You set technical direction across the full arc of applied science. That means framing problems, making architecture decisions, defining how the team evaluates quality, and delivering solutions in production. The ideal candidate pairs deep machine learning expertise with a builder's instinct for production architecture. They thrive on ambiguity, mentor others, and follow a fast-moving research frontier.

About the team

Internal Audit’s mission is to help our businesses improve controllership, operational efficiency, and customer experience.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience building complex software systems that have been successfully delivered to customers
• Experience architecting/operating solutions built on AWS, or experience implementing a cloud-based technology solution

Preferred Qualifications

• Experience using Unix/Linux
• Experience in professional software development
• Experience designing and running evaluation frameworks for generative AI (e.g., LLM-as-judge, human-alignment measurement, benchmarking output quality).
• Hands-on experience with agentic AI frameworks and generative AI services (e.g., Amazon Bedrock, SageMaker, LangGraph, Strands).
• Experience building and maintaining production ML/AI infrastructure — deployment pipelines, observability/tracing, and experimentation environments.
• A track record of applied-research output: publications, conference talks, or patents.

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. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually