Sharavan Mudaliar
Analyst — AI/LLM Practice
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About
Utilize RLHF to evaluate multi-modal data (text, image, audio) against strict safety rubrics, identifying bias, hallucinations, and harmful content to optimize LLM grounding. Execute complex dialogue evaluation and prompt-response ranking via the MultiTango platform, making logical decisions on ambiguous edge cases to generate high-fidelity ground truth data. Perform root-cause analysis on error patterns and collaborate with governance leads to update Standard Operating Procedures (SOPs) and safety guidelines.
Experience
Analyst — AI/LLM Practice at Innodata India (2026-12 – Present)
- Utilize RLHF to evaluate multi-modal data (text, image, audio) against strict safety rubrics, identifying bias, hallucinations, and harmful content to optimize LLM grounding.
- Execute complex dialogue evaluation and prompt-response ranking via the MultiTango platform, making logical decisions on ambiguous edge cases to generate high-fidelity ground truth data.
- Perform root-cause analysis on error patterns and collaborate with governance leads to update Standard Operating Procedures (SOPs) and safety guidelines.
Data Annotator at Innodata India (2025-11 – 2025-12)
- Executed high-volume text categorization, image labeling, and search relevance tasks with 95% quality standard compliance, ensuring clean data collection.
- Conducted fact-checking and data auditing using internal tools, strictly adhering to dynamic instructions, SLAs, and data confidentiality protocols.
- Consistently met productivity baselines while making sound judgments on ambiguous information, raising execution queries proactively to resolve operational bottlenecks.
Education
Master of Computer Applications in MCA – SIES College of Management Studies (SIESCOMS) (2024-08 – 2026-06)
Bachelor of Science in Computer Science – SIES College of Arts, Science and Commerce (2021-08 – 2024-05)
