Machine Learning Engineer, AppStar Data Analytics & Engineering
Amazon•Published 1 days ago•First seen 2 hours ago
The AppStar Data Analytics & Engineering (DNA) team within Amazon's Application Security organization is seeking a Machine Learning Engineer II to build, deploy, and scale ML systems that power how Amazon prioritizes and manages application security risk.
You will own the end-to-end ML lifecycle: training and tuning models, building robust data pipelines, deploying models into production, and monitoring their performance at scale. Our team builds risk-scoring models, complexity-assessment systems, and graph-based intelligence layers that directly determine which applications receive security attention. This is hands-on engineering with direct, measurable impact on Amazon's security posture.
The ideal candidate has strong software engineering fundamentals, experience deploying ML models in production environments, and a desire to work at the intersection of machine learning and security operations. You'll collaborate closely with applied scientists, data engineers, and security engineers to translate research into scalable, production-grade ML services on AWS.
Key job responsibilities
- Design, build, and maintain production ML pipelines (feature extraction, model training, scoring, serving) using AWS services such as SageMaker, Glue, S3, and Athena
- Implement and deploy ML models for application security risk scoring, complexity assessment, and classification at scale
- Develop scalable data processing systems that ingest, transform, and serve features from large-scale security datasets
- Architect distributed computing solutions for model training and inference, leveraging Spark/PySpark and AWS infrastructure
- Monitor model performance in production, implement drift detection, and drive continuous improvement through retraining and tuning
- Partner with applied scientists to operationalize research prototypes into reliable, maintainable production services
- Apply software engineering best practices: write testable, well-documented code, conduct peer reviews, and maintain operational excellence
- Contribute to the team's ML infrastructure and tooling to improve development velocity and model reliability
About the team
The Data Analytics & Engineering (DNA) team is a small, high-impact group within Amazon's Application Security organization. We build ML models, graph-based systems, and analytics platforms that determine how Amazon prioritizes security coverage across tens of thousands of applications. We're builders who ship production ML, embrace ambiguity in messy security data, and operate with high ownership.
Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why Amazon Security?
At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.
Inclusive Team Culture
In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.
Training & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
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.
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
You will own the end-to-end ML lifecycle: training and tuning models, building robust data pipelines, deploying models into production, and monitoring their performance at scale. Our team builds risk-scoring models, complexity-assessment systems, and graph-based intelligence layers that directly determine which applications receive security attention. This is hands-on engineering with direct, measurable impact on Amazon's security posture.
The ideal candidate has strong software engineering fundamentals, experience deploying ML models in production environments, and a desire to work at the intersection of machine learning and security operations. You'll collaborate closely with applied scientists, data engineers, and security engineers to translate research into scalable, production-grade ML services on AWS.
Key job responsibilities
- Design, build, and maintain production ML pipelines (feature extraction, model training, scoring, serving) using AWS services such as SageMaker, Glue, S3, and Athena
- Implement and deploy ML models for application security risk scoring, complexity assessment, and classification at scale
- Develop scalable data processing systems that ingest, transform, and serve features from large-scale security datasets
- Architect distributed computing solutions for model training and inference, leveraging Spark/PySpark and AWS infrastructure
- Monitor model performance in production, implement drift detection, and drive continuous improvement through retraining and tuning
- Partner with applied scientists to operationalize research prototypes into reliable, maintainable production services
- Apply software engineering best practices: write testable, well-documented code, conduct peer reviews, and maintain operational excellence
- Contribute to the team's ML infrastructure and tooling to improve development velocity and model reliability
About the team
The Data Analytics & Engineering (DNA) team is a small, high-impact group within Amazon's Application Security organization. We build ML models, graph-based systems, and analytics platforms that determine how Amazon prioritizes security coverage across tens of thousands of applications. We're builders who ship production ML, embrace ambiguity in messy security data, and operate with high ownership.
Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why Amazon Security?
At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.
Inclusive Team Culture
In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.
Training & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Basic Qualifications
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
- 1+ years of Object Oriented Design experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience programming with at least one software programming language
Preferred Qualifications
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. 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, NY, New York - 158,100.00 - 213,800.00 USD annually