Amazon is building next generation software, hardware, and processes that will run our global network of fulfillment centers that move millions of units of inventory, and ensure customers get what they want when promised.

The Business Analytics and Decision Support (BADS) team automates the ingestion and curation of data for analyses, business reviews and operational reporting demands. Our north star is to enable and leverage the power of data to drive informed decision-making and value through analytical and scientifically derived insights and innovative solutions and processes.

As a Machine Learning Engineer within our BADS team, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge (around machine learning, natural language processing, computer vision), technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations releases into production. While ensuring CI/CD compliance and ensuring best practices in software development and cloud infrastructure are followed (in the realm of scalability, security and availability).

Key job responsibilities
- Own the development and operationalization of solutions deployed in production.
- Work across multiple teams to integrate our solutions with products owned by our partners.
- Design model experimentation processes and frameworks in synergy with our scientists.
- Help the team grow and cultivate best practices in software development, MLOps, and experimentation.

A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!


- 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
- Experience programming with at least one software programming language
- 2+ years of experience with the AWS CDK or SDK
- 1+ year’s experience and knowledge in MLOps, in deploying, operationalizing, and maintaining scalable AI/ML-solutions in production
- Prior experience developing and implementing scalable machine learning solutions with technologies such as AWS SageMaker, EMR, S3, Lambda, Airflow and CI/CD Pipeline

- 3+ 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
- Experience with ML libraries/frameworks such as Tensorflow, AWS Sagemaker, Keras, PyTorch, etc.
- Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.