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Key job responsibilities
As an Applied Scientist in Search and Shopping, you will have deep expertise in machine learning and data science, with specialties in large language models, reinforcement learning, supervised learning, and generative AI across various modalities. This role involves aligning solutions with multiple partners including product teams, experience design and foundational model teams. You will lead teams of scientists and engineers in translating business and functional requirements into concrete deliverables, driving strategic initiatives to enhance AI-driven customer experiences.Your responsibilities include designing integrated solutions that are efficiently implemented across the stakeholder teams, maintaining alignment in the short term while influencing long-term strategic roadmaps to support ongoing experimentation. You will ensure high solution quality, focusing on accurately understanding and responding to customers through Search and AI assistants, enhancing the speed of experiments and iterations of customer experience.Additionally, this role involves building scalable solutions with robust checks on human feedback, managing the complexities of customer intents, and reinforcing learning algorithms with human feedback. You will make critical decisions on the best technical solutions for both immediate and future needs, clarify complex issues, manage trade-offs, and communicate effectively about technical challenges.Finally, you will work with academic partners to enhance our team's capabilities by accessing the latest research and expert mentoring, ensuring our approaches remain cutting-edge.
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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