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Key job responsibilities
A Research Engineer in the AWS AI team has the following responsibilities: * Define, design and lead the development of tools that accelerate the science experimentation and delivery process
* Design and guide the science team's implementation, enabling Science proof of concepts that help decide the ultimate science solution strategy, algorithm workflow, and the individual science components that become a release candidate
* Tool development: build and improve toolings that applied scientists would need, including scalable science experiment frameworks, low-latency testing pipelines, data collection/annotation/evaluation web applications.
* Expedite science to production: bridge the gap between science and engineering teams, help to investigate and mitigate gaps between science and engineering pipeline. Help to merge both pipelines to one, or making components within the two interchangeable. Work towards a fast science-to-production paradigm. About the team
Diverse Experiences
Amazon 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, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS Work/Life Balance Inclusive Team Culture Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
- 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
- Bachelor's degree in computer science or equivalent
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
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