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Sujith Julakanti
Junior MLOps Engineer specializing in LLMs and cloud infrastructure
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Built a production multimodal LLM system (Gemini on GCP) to automate behavioral coding of family-involved science experiment videos, including preprocessing for inconsistent lighting/audio and LangGraph-orchestrated parallel workflows. Also developed rubric-based AI grading workflows and partnered closely with non-technical education stakeholders through explainability-focused walkthroughs and manual-vs-AI evaluation alignment.
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Key Strengths
- Built and deployed a multimodal LLM pipeline to auto-code 500+ short science-experiment videos into behavioral categories
- Handled real-world multimodal data issues via video/audio preprocessing and normalization across varying lighting and audio conditions
- Designed orchestrated agent workflows using DAG/state-machine patterns with clear failure boundaries and debuggability
- Improved model accuracy by adding whole-video summarization to provide global context before per-segment classification
- Effective collaboration with non-technical education stakeholders by translating AI outputs into rubric/partial-credit logic and running manual-vs-AI grading comparisons
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Experience
Education
Awards
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Publications
1 publication
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