Partner with Applied and Research Scientists to operationalize ML workflows, including feature delivery, training data preparation, and model-scoring pipelines.
Deliver robust, well-tested, production-quality software and drive engineering best practices (code reviews, Continuous Integration/Continuous Deployment (CI/CD), monitoring, operational excellence).
Diagnose and resolve complex production and data issues; participate in on-call and reduce operational load through automation.
Mentor SDE I and early-career engineers and influence the technical roadmap for the team's data platform.
About the team
Amazon Fulfillment Technologies (AFT) Inbound builds the software and science that move inventory into Amazon's fulfillment network — from the moment a supplier ships product to the point it's received, stowed, and ready to fulfill customer orders. Operating at the scale of billions of units across a global network of fulfillment centers, our team owns the data infrastructure and intelligent systems that make inbound flow faster, more accurate, and more cost-efficient. We work at the intersection of large-scale data engineering and applied Machine Learning (ML), partnering closely with Applied and Research Scientists to turn petabytes of supply-chain data into decisions that ship every day. If you're excited by hard distributed-systems problems, real-world scale, and building the data foundations that power automation and optimization across Amazon's supply chain, you'll find a high-ownership, high-impact home here.
3+ years of building complex software systems experience
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
Strong Python proficiency and experience with SQL at scale
Experience building and owning batch and streaming data pipelines in production environments
Experience with big data technologies (Spark, Hive, Presto, or similar distributed computing frameworks)
Experience building data models and ETL/ELT pipelines that serve both analytics/reporting and ML workloads (feature engineering, preprocessing, training data management)
Experience collaborating with science or ML teams to take models from prototype to production (training data preparation, feature delivery, model-scoring pipelines)
Experience with data quality, validation, or observability practices for production datasets
Experience using AI coding assistants or agentic development tools (e.g., Amazon Q Developer, Copilot, Kiro, or similar) to accelerate software delivery
Solid software engineering fundamentals (testing, CI/CD, code review, production operations)
Experience deploying ML models to production environments
Experience designing and optimizing large-scale data architectures (data lakes, data warehouses, lakehouse patterns)
Experience with MLOps tooling (SageMaker Pipelines, Step Functions, MLflow, or similar) for operationalizing model training, scoring, and deployment workflows
Experience partnering cross-team with SDEs to design and ship ML-integrated services or systems
Experience using agentic workflows to generate, test, and iterate on code, infrastructure, or pipeline components at scale
Experience with prompt engineering and LLM APIs
Experience with ML evaluation frameworks (especially for generative AI / LLM outputs)
Experience with data lineage, cataloging, and observability tooling at scale
Experience with streaming data processing (Kafka, Kinesis, Flink)
Experience with data orchestration tools (Airflow, Step Functions, AWS Glue workflows)
Experience with infrastructure-as-code (CDK, CloudFormation, Terraform)
Experience building metrics and reporting infrastructure consumed by business stakeholders
Background in supply-chain, logistics, fulfillment, or operational environments
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, WA, Bellevue - 143,700.00 - 194,400.00 USD annually
