Senior Machine Learning Engineer, Sustainability Science and Innovation

Amazon.com Services LLC; Seattle (WA); On-site; USD 168,000 - 227,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

RSUs

Sign-on payments

Parental leave

Mental Health Support

Job summary

Amazon.com Services LLC in Seattle, WA is seeking a Senior Machine Learning Engineer to build software and infrastructure that enables scientists to develop, evaluate, and deploy ML models for sustainability applications.

You will work across research workflows and production systems, creating AI-assisted tooling, reusable data and ML infrastructure, and scalable design patterns to support reliable, repeatable experiments.

Qualifications

• 5+ years of professional software development experience.
• 5+ years of programming experience in at least one language.
• 5+ years of leading design or architecture for new and existing systems.
• Experience as a mentor, tech lead, or in leading an engineering team.
• 5+ years of full software development life cycle experience.

Responsibilities

• Build reusable data and ML infrastructure for data processing, model training, and inference.
• Create tools for repeatable experiments and model comparisons with data, code, and configuration.
• Develop and evaluate AI-assisted workflows to help coding agents use the platform correctly.
• Assess coding agent output with automated checks and reviews to maintain reliability.
• Support adoption by documenting trade-offs and maintaining compatibility as components evolve.

Education

Bachelor’s degree in computer science or equivalent

Job description

Amazon.com Services LLC is seeking a Senior Machine Learning Engineer to build software and infrastructure that enables scientists to develop, evaluate, and deploy machine learning models for sustainability applications. This onsite role is based in Seattle, WA and spans both research workflows and production systems.

Role Summary

In this position, you will develop AI-assisted engineering interfaces and workflows that include checks for reliability. You will also create systems that support repeatable experimentation, model comparison, and safe integration of automated coding agents into the platform.

Key Responsibilities

• Build reusable data and machine learning infrastructure, including libraries, configuration-driven interfaces, and infrastructure-as-code components for data processing, model training, and inference.
• Create tools that enable repeatable experiments and model comparisons, preserving the data, code, and configuration required to investigate results.
• Develop and evaluate AI-assisted workflows by building tooling that helps coding agents use the platform correctly.
• Assess coding agent output using automated checks and appropriate review, and measure whether the workflows improve engineering productivity without weakening reliability.
• Support adoption and evolution by working with platform users to identify recurring needs, document design trade-offs, and maintain compatibility as shared components change.

Required Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with experience in at least one software programming language.
• 5+ years of leading design or architecture, including design patterns, reliability, and scaling, for new and existing systems.
• Experience as a mentor, tech lead, or in leading an engineering team.
• 5+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Bachelor’s degree in computer science or equivalent.

Compensation

USD 168,100 - 227,400 per year

Benefits

• Health insurance: medical, dental, vision, prescription, Basic Life & AD&D, with 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
• Sign-on payments
• Restricted stock units (RSUs)

About the Team

• The team combines applied scientists and engineers to develop models and software for sustainability applications.
• Work spans both research and production, building scientific methods and the systems required to use them reliably.
• Reusable tools are built so new research projects do not require their own infrastructure.