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Shardul Jeurkar
Intern Applied AI/Software Engineer specializing in computer vision and full-stack platforms
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About
Built production LLM systems focused on reliability and safety, including a plain-English deployment tool that generates validated plans and provisions to Kubernetes while preventing unsafe actions via schema enforcement and plan/execute separation. Also created multi-LLM workflows (LangGraph) and stakeholder-friendly demos at Bosch, including a PyQt/FastAPI/CUDA app comparing SAM2 vs SAMWISE for on-device object detection with intuitive UX for business users.
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Key Strengths
- Built and deployed an LLM-driven natural-language-to-Kubernetes deployment system
- Strong safety controls: schema-constrained JSON outputs and separation of planning vs execution to prevent unsafe actions
- Designs agent workflows as deterministic/state-machine processes with explicit accept/reject conditions
- Defines measurable reliability metrics per workflow state (cost, tokens, success rate, retry/failure rate) and validates via unit/integration tests
- Applied multi-LLM orchestration with automated quality gating (LLM generation + LLM judge + iterative redo loop) using LangGraph
- Effective collaboration with non-technical stakeholders via intuitive demos (PyQt/FastAPI app showcasing SAM2 vs SAMWISE with simple interactions)
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Experience
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Publications
2 publications
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