Machine Learning Engineer, Insights, Data Engineering, Econometrics, Analytics & Science (IDEAS)
Machine Learning Engineer, Insights, Data Engineering, Econometrics, Analytics & Science (IDEAS)
Posted on :
07-06-2025
Employer Active
1 Vacancy
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Yearly Salary
$ 129300 - 223600
Vacancy
1 Vacancy
Posted on :
07-06-2025
Job Description
Amazon is seeking an experienced self-directed machine learning data engineer to support the research and analytical needs of Amazon Web Services Sales teams. This is a unique opportunity to invent new ways of leveraging our large complex data streams to automate sales efforts and to accelerate our customers journey to the cloud. This is a high-visibility role with significant impact potential.
About AWS:
Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (cloud computing). With AWS you can requisition compute power storage and many other services gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform.
About you:
You as the right candidate are adept at productionalizing and scaling innovative high-performance machine learning (ML) and statistics solutions that solve business problems at massive scale. You have carried projects from proof-of-concept to deployment and prediction serving with a high standard for model maintenance and operations. You have turned large volumes of structured and unstructured data into training and prediction sets. You have orchestrated complex and/or distributed modeling systems to unlock new ML capabilities for your customers. You have a strong grasp of popular machine learning and data processing frameworks. You have developed maintainable reusable components and microservices as part of your pipelines that unlock speed scale and integration for others. You are talented at communicating technical concepts clearly to stakeholders in concise non-technical language.
GSO2024
Key job responsibilities
What you will do:
- Work with a team of business analysts data scientists and engineers to bring ML and statistics solutions to our Sales teams
- Develop and deploy models and pipelines that scale
- Use AWS services like SageMaker EMR ECS Glue and more to build and deploy scalable machine learning models in the cloud
A day in the life
Example projects:
- Scaling out and deploying regression classification and recommendation models
- Developing reusable cloud infrastructure and deployment patterns to accelerate productionalization
- Integrating disparate ML solutions into cohesive customer experiences
About the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.
About Sales Marketing and Global Services (SMGS)
AWS Sales Marketing and Global Services (SMGS) is responsible for driving revenue adoption and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
- 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
- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Bachelors degree in computer science or equivalent
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129300/year in our lowest geographic market up to $223600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity sign-on payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
About AWS:
Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (cloud computing). With AWS you can requisition compute power storage and many other services gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform.
About you:
You as the right candidate are adept at productionalizing and scaling innovative high-performance machine learning (ML) and statistics solutions that solve business problems at massive scale. You have carried projects from proof-of-concept to deployment and prediction serving with a high standard for model maintenance and operations. You have turned large volumes of structured and unstructured data into training and prediction sets. You have orchestrated complex and/or distributed modeling systems to unlock new ML capabilities for your customers. You have a strong grasp of popular machine learning and data processing frameworks. You have developed maintainable reusable components and microservices as part of your pipelines that unlock speed scale and integration for others. You are talented at communicating technical concepts clearly to stakeholders in concise non-technical language.
GSO2024
Key job responsibilities
What you will do:
- Work with a team of business analysts data scientists and engineers to bring ML and statistics solutions to our Sales teams
- Develop and deploy models and pipelines that scale
- Use AWS services like SageMaker EMR ECS Glue and more to build and deploy scalable machine learning models in the cloud
A day in the life
Example projects:
- Scaling out and deploying regression classification and recommendation models
- Developing reusable cloud infrastructure and deployment patterns to accelerate productionalization
- Integrating disparate ML solutions into cohesive customer experiences
About the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.
About Sales Marketing and Global Services (SMGS)
AWS Sales Marketing and Global Services (SMGS) is responsible for driving revenue adoption and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
- 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
- 3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Bachelors degree in computer science or equivalent
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129300/year in our lowest geographic market up to $223600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity sign-on payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
Employment Type
Full-Time
Department / Functional Area
Key Skills
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