Sr. SDE, SageMaker AI
Bellevue, Washington, USA
Full Time Senior-level / Expert USD 151K - 261K
Amazon.com
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Are you a highly skilled and innovative Software Development Engineer with a passion for developing new machine learning capabilities and driving innovation to build customer-centric solutions in Amazon SageMaker AI? Are you interested to play a key role in developing software applications at AWS? We invite you to join us and be part of making history.
The Amazon SageMaker Pipelines team is seeking highly skilled and innovative Software Development Engineer to join our organization. SageMaker Pipelines provides a serverless workflow orchestration capability purpose-built for MLOps/LLMOps automation. This capability enables our customers to easily build, execute, and monitor repeatable end-to-end machine learning workflows through an intuitive API, drag-and-drop UI, and the Python SDK. In this role, you will be responsible for building and maintaining capabilities within our best-in-class machine learning offering, as well as scaling those systems to support our customers' workflow orchestration automation needs.
Engineers on the Amazon SageMaker Pipelines team are expected to consistently experiment with new technologies and ideas in order to drive innovation and ensure SageMaker remains a best-in-class service. You will be held to the highest standards of engineering and operational excellence, including building highly resilient and scalable systems, producing clear and effective technical documentation, actively contributing to discussions on strategic direction, and continuously raising the bar. Most importantly, you will have the opportunity to collaborate with a team of highly skilled and dedicated engineers who share a commitment to achieving new levels of success.
About Amazon SageMaker AI
Amazon SageMaker AI is a fully managed machine learning service that simplifies the process of building, training, and deploying machine learning models. It abstracts away the undifferentiated heavy-lifting associated with large-scale machine learning implementations, allowing developers and data scientists to focus on the core modeling and problem-solving aspects of their work. SageMaker is currently utilized by businesses of all sizes, including some of the world's leading enterprises, across a growing number of geographic regions.
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Bachelor's 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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
The Amazon SageMaker Pipelines team is seeking highly skilled and innovative Software Development Engineer to join our organization. SageMaker Pipelines provides a serverless workflow orchestration capability purpose-built for MLOps/LLMOps automation. This capability enables our customers to easily build, execute, and monitor repeatable end-to-end machine learning workflows through an intuitive API, drag-and-drop UI, and the Python SDK. In this role, you will be responsible for building and maintaining capabilities within our best-in-class machine learning offering, as well as scaling those systems to support our customers' workflow orchestration automation needs.
Engineers on the Amazon SageMaker Pipelines team are expected to consistently experiment with new technologies and ideas in order to drive innovation and ensure SageMaker remains a best-in-class service. You will be held to the highest standards of engineering and operational excellence, including building highly resilient and scalable systems, producing clear and effective technical documentation, actively contributing to discussions on strategic direction, and continuously raising the bar. Most importantly, you will have the opportunity to collaborate with a team of highly skilled and dedicated engineers who share a commitment to achieving new levels of success.
About Amazon SageMaker AI
Amazon SageMaker AI is a fully managed machine learning service that simplifies the process of building, training, and deploying machine learning models. It abstracts away the undifferentiated heavy-lifting associated with large-scale machine learning implementations, allowing developers and data scientists to focus on the core modeling and problem-solving aspects of their work. SageMaker is currently utilized by businesses of all sizes, including some of the world's leading enterprises, across a growing number of geographic regions.
Basic Qualifications
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
Preferred Qualifications
- 5+ 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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Category:
Deep Learning Jobs
Tags: APIs Architecture AWS Computer Science Engineering LLMOps Machine Learning ML models MLOps Pipelines Python SageMaker SDLC Testing
Perks/benefits: Career development Equity / stock options
Region:
North America
Country:
United States
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