Amazon Principal Applied Scientist AGI Foundations 

United States, California, Sunnyvale 

737559956

You will also help drive scalable, robust, and automated solutions, leading scientists to make new algorithms and processes scalable to work on production-scale data sizes and achieving fully automated adaptation of processes and algorithms to new environments and locales. You will also lead integration of new algorithms and processes into existing modeling stacks, simplify and streamline the existing modeling stacks, and develop testing and evaluation strategies. You will influence design and architecture of software stacks used offline and at runtime for building and deploying model artifacts, achieving flexible yet efficient solutions suitable for R&D work and for running in production. You will mentor scientists and review scientific work in other organizations to raise the bar of scientific research within Amazon.Key job responsibilities
You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

PhD with specialization in artificial intelligence, natural language processing, machine learning, or computational cognitive science 10+ years of combined academic and research experience. Strong publication record in top-tier journals and conferences. Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. Mentors and trains the research scientist community on complex technical issues. Experience developing software in traditional programming languages (C++, Java, etc..). Excellent written and spoken communication skills