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Utility Computing (UC)Key job responsibilities
As a member of the ML chip architecture team, you will be responsible for accelerating large-scale machine learning workloads holistically across algorithms, software, and hardware, as part of our continuous effort to deliver a world-class customer experience. You will be the interface between SW and HW teams, bridging the gap between silicon capabilities and application requirements. Finally, you will have a chance to drive performance improvements on existing AWS hardware platforms, as well as propose, evaluate, and develop hardware optimizations targeting future generations of our products.Internal job descriptionAbout the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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 BalanceMentorship 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.
- Knowledge of computer science fundamentals such as object-oriented design, operating systems, algorithms, data structures, and complexity analysis
- Are 18 years of age or older
- Experience with at least one modern language such as Java, Python, C++, or C# including object-oriented design
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience with distributed, multi-tiered systems, algorithms, and relational databases
- Experience in optimization mathematics such as linear programming and nonlinear optimization
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