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Peeyush Dyavarashetty
Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems
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About
AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.
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Key Strengths
- Built a GPT-2-like LLM from scratch in PyTorch, including architecture and loss function work
- Hands-on experience scaling training/validation across multiple GPUs (distributed training)
- Diagnosed and mitigated training slowdowns/stalls by separating training and validation workflows
- Implemented experiment tracking and visualization for model performance using Weights & Biases
- Designed and shipped multiple AI-agent automation workflows (Gmail classification; Fireflies-to-Claude task extraction for CEO)
- Established structured evaluation process for AI agents using test cases and metrics (accuracy/precision/recall) plus relevance of assigned tasks
- Effective iteration with a non-technical stakeholder (CEO) to translate business needs into AI agent capabilities
Reference Highlights
- Thorough in understanding requirements and details before proposing solutions
- Effective collaboration with non-technical stakeholders
- Clear, structured technical explanations (explains purpose of tools/services before solutions)
- Communicates rationale for choosing one tool over another
- Avoids repetitive explanations
- Contributed to taking an LLM-based product to production on AWS
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