Akhilesh Padala

About

ML/AI engineer with strong end-to-end production ownership across predictive ML and Generative AI use cases. They built a churn prediction platform that cut churn 12% and preserved about $1.2M in annual revenue, and also shipped a RAG-based support assistant that reduced ticket resolution time 30% while improving agent satisfaction and onboarding speed.

Key Strengths

• End-to-end ownership of production ML systems
• Built churn prediction system that reduced customer churn by 12%
• Improved retention by 18% in top-value segment
• Drove approximately $1.2M in annual retained revenue
• Increased retention team efficiency by 25%
• Shipped RAG-based LLM support assistant
• Reduced ticket resolution time by 30%
• Improved agent satisfaction by 25%
• Cut new-agent onboarding time by nearly 50%
• Translated research into scalable transformer-based production systems
• Reduced model latency by 60% via distillation with only 2% accuracy loss
• Lowered inference cost by 30% through dynamic batching and autoscaling
• Strong MLOps and monitoring discipline
• Built reusable Python model-serving infrastructure with 90%+ test coverage

Experience

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