Innovative AI Professional

4 days ago

lucknow, India beBeeArtificial Full time

AI Innovation SpecialistThe AI Grant Evaluation & Research Specialist will play a critical role in advancing initiatives to improve grant-writing success through AI-assisted scoring, analysis, and content generation.This role is responsible for refining scoring systems, developing and validating evaluative rubrics, analyzing funded vs. unfunded grant trends, and collaborating with subject matter experts to evolve an enterprise-ready AI solution for grant evaluation and writing support.Key Responsibilities:Grant Scoring System Development & EnhancementAi Model Collaboration, ML/DL Integration & Prompt EngineeringResearch, Data Analysis & Model EvaluationCross-Functional CollaborationFuture Development & System ExpansionRequired Skills & Qualifications:Technical (ML/DL) Skills:• Strong understanding of machine learning fundamentals: supervised/unsupervised learning, evaluation metrics, feature engineering.• Experience with deep learning architectures: transformers, CNNs, RNN/LSTM, encoder–decoder models.• Hands-on experience with LLMs or generative AI platforms.• Familiarity with frameworks such as PyTorch, TensorFlow, Hugging Face, or similar.• Ability to evaluate model outputs and apply systematic error analysis.• Experience working with text datasets, NLP pipelines, and embedding techniques.Analytical & Writing Skills:• Strong analytical ability to identify differentiators in written material quality.• Experience designing or improving rubric-based evaluation systems.• Exceptional written communication skills.• Understanding of grant writing fundamentals and funder priorities.Collaboration & Project Management:• Ability to work cross-functionally with SMEs, technical teams, and grant-writing staff.• Strong attention to detail and ability to manage iterative testing processes.• Comfort working in environments requiring rapid experimentation and model refinement.Preferred Qualifications:Experience with custom GPT development, prompt engineering, or model fine-tuning.Background in educational grants, research funding, healthcare education, or nonprofit grant systems.Familiarity with data tools or ML ops platforms for model development and deployment.Success Indicators:Improved accuracy, reliability, and adoption of AI grant-scoring and writing systems.Enhanced rubric effectiveness and data-driven scoring logic.Clear model improvements through ML/DL-driven refinements.Tangible contributions to automated grant writing capabilities.Strong cross-team satisfaction and system usability.

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