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Job Description
- Design, develop, and deploy scalable and robust agentic AI solutions for high-value, real-world enterprise use cases across domains like finance, sales, marketing, and retail, focusing on innovation and utility, with a user-centric perspective.
- Drive progress through rapid experimentation cycles. This includes proposing hypotheses, designing validation methods, implementing and testing ideas, analyzing results, and iterating quickly to find optimal solutions.
- Contribute to significant advancements in key research areas such as reinforcement learning, multi-modal learning, benchmarking and evals, search/retrieval, adaptation methods for agentic systems, and improving the reliability and tool-use capabilities of LLMs for enterprise-critical tasks to build.
- Handle ambiguous problems with creative, AI-driven solutions.
- Debug, track, and resolve issues efficiently to ensure the high reliability and performance of the AI systems.