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. Major Duties and Responsibilities: Develop, maintain, and operationalize geospatial data science pipelines across ingestion, feature engineering, training, inference, evaluation, and delivery, using
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, inference). Develop agentic AI systems and AI harnessing techniques to enhance model quality, resource optimization, and adaptive execution in diverse workflows. Investigate strategies to balance performance
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, multidisciplinary team environment. Preferred Qualifications: Knowledge of uncertainty quantification methods and causal inference for complex environmental systems. Experience with large-scale Earth system
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generative AI/LLMs, including RAG systems Familiarity with LLM inference servers (e.g., vLLM, Ollama) Hands-on benchmarking/Test & Evaluation of AI systems Data visualization and dashboarding (e.g., Streamlit
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descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other