● Owned and scaled ML data pipelines that significantly boosted annotation efficiency (~40% faster) while improving data reliability across enterprise workflows.
● Built intelligent LLM evaluation systems with RLHF loops, driving measurable improvements in model alignment and real-world performance.
● Reimagined data lifecycle processes (ingestion to validation), cutting delays by 35% and enabling faster, higher-quality model training.
● Acted as a bridge between engineering, product, and business teams to translate AI requirements into scalable solutions.
● Introduced data-driven decision systems (KPIs & dashboards) to improve visibility into model and operational performance.
● Drove adoption of GenAI-first workflows, accelerating experimentation and innovation across teams.
● Designed scalable, cloud-native ML systems ensuring reliability, security, and high availability.
● Played a key role in roadmap execution, prioritization, and continuous delivery in fast-paced AI environments