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A day in the lifeDiverse 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.Mentorship & 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.Work/Life Balance
- 2+ years of building machine learning models or developing algorithms for business application experience
- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Working knowledge of generative AI and hands on experience in prompt engineering, deploying and hosting Large Foundational Models
- Hands on experience building models with deep learning frameworks like Tensorflow, PyTorch, or MXNet
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