Geetha Pranavi Tulam

Experience

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  Accenture

  Jul 2017 - Aug 2022

  AI/ML Engineer

  ▪ Led a team of 20 employees, overseeing performance reviews, goal setting, and mentoring. I provided weekly performance insights, identified skill gaps, and conducted targeted training sessions that resulted in a 15% increase in team productivity and retention.▪ Spearheaded a data collection and feature engineering initiative to enhance the machine learning pipeline's data quality. By improving feature selection and cleaning processes, the accuracy of predictive models improved by 12%, directly impacting content review efficiency.▪ Developed an ML-based performance evaluation system for internal review processes. The system identified top performers and areas of improvement, resulting in a 10% boost in overall team performance and better alignment with company objectives.▪ Designed and implemented dynamic dashboards to track compliance and operational metrics using similar dashboards like Power BI. These dashboards improved visibility across teams and resulted in a 20% increase in operational efficiency by allowing quicker decision-making andreal-time monitoring.▪ Integrated advanced text analytics to automate the review of unstructured data in content workflows, which reduced human errors by 15% and sped up content review processes by over 10%. Show less

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  Svasti.AI

  Aug 2024 - Sept 2024

  AI/ML Intern

  ▪ Developed an image-to-text conversion system using Ollama and LLava-LLaMA 3, which significantly improved the accuracy and speed of extracting textual content from complex image datasets.▪ Optimized the preprocessing pipeline by automating the transformation of image data into structured formats, reducing manual effort by 20%.

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  RICEFW Technologies Inc

  Sept 2024 - now

  AI/ML Intern

  ▪ Currently developing a conversational chatbot using Azure AI Studio, focused on automating customer service tasks and handling complex queries in a multilingual environment.▪ Leveraging Azure’s cognitive services and AI-powered APIs to build a scalable, intelligent chatbot, collaborating with product and customer support teams to refine performance, resulting in a projected 20% reduction in customer response time.