Software Development Engineer, AWS AmazonAI Machine Learning Platform
Bellevue, Washington, USA
Amazon.com
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Job summary
Are you interested in democratizing machine learning? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to empower data scientists and software engineers in their machine learning endeavors. Amazon SageMaker Autopilot (https://aws.amazon.com/sagemaker/autopilot/) allows you to automatically build machine learning models. SageMaker Autopilot will automatically explore different solutions to find the best model based on the data you provide.
You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers.
We're moving fast, and this is a great team to come to have a huge impact on AWS and the world's customers we serve!
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
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
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Are you interested in democratizing machine learning? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to empower data scientists and software engineers in their machine learning endeavors. Amazon SageMaker Autopilot (https://aws.amazon.com/sagemaker/autopilot/) allows you to automatically build machine learning models. SageMaker Autopilot will automatically explore different solutions to find the best model based on the data you provide.
You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers.
We're moving fast, and this is a great team to come to have a huge impact on AWS and the world's customers we serve!
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Basic Qualifications
- 1+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems.
- 2+ years of non-internship professional software development experience
- Programming experience with at least one software programming language.
- Bachelor’s Degree in Computer Science or related field
- 8+ years of professional experience in software development
- Experience in mentoring junior software engineers to improve their skills, and make them more effective, product software engineers
- Experience in data structures, algorithm design, complexity analysis, object-oriented design
- Proficiency in at least one modern programming language such as Java, Scala, Python, C++, C#
- Experience in professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
- Experience with building complex software systems that have been successfully delivered to customers
- Proven ability to take a project from scoping requirements through actual launch of the project, with experience in the subsequent operation of the system in production
Preferred Qualifications
- Experience with machine learning and/or data engineering
- Ability to take a project from scoping requirements through actual launch of the project
- Master's degree in Computer Science, Computer or Electrical Engineering
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
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Tags: Architecture AWS Computer Science Engineering Machine Learning ML models Python SageMaker Scala Testing
Perks/benefits: Conferences
Region:
North America
Country:
United States
Job stats:
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Categories:
Deep Learning Jobs
Engineering Jobs
Machine Learning Jobs
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