Research Scientist, Applied AI

Аналитика рынка

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Описание

Accountabilities - Own and advance the agent harness, including its core execution loop, tools, operating environment, guardrails, and model behavior. - Improve tool selection, context construction, coordination across sub-agents, and the handling of complex, long-running tasks through systematic experimentation. - Evaluate and select models for different tasks, balancing output quality, latency, and computational cost. - Design and implement evaluation frameworks for complex revenue-related tasks, including deal health, risk assessment, and pipeline analysis. - Develop evaluation datasets, benchmarks, grading methodologies, regression detection systems, and automated evaluation pipelines, particularly for tasks without clear ground truth. - Build predictive and scoring models using data from call transcripts, emails, and other business signals to identify cross-deal patterns and generate explainable risk indicators. - Lead model fine-tuning initiatives and advance the platform toward deeper model training and reinforcement learning. - Research and implement reinforcement learning approaches to improve agent performance and decision-making. - Strengthen context engineering and data quality through entity resolution, information extraction, and the development of knowledge and context graphs. - Take ownership of ambiguous research challenges from initial hypothesis and experimental design through training infrastructure, evaluation, and production deployment. - Collaborate clo

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