Machine Learning Software Engineer

AKSHATA ASHOK JEDHE

+1-623-***-**** **************@*****.*** linkedin.com/in/akshatajedhe github.com/akshataj28 EDUCATION

Master of Science in Computer Science Expected May 2025 Arizona State University, Tempe, AZ. GPA: 3.6/4.0

Courses: Artificial Intelligence, Generative AI, Machine Learning, Distributed Systems, Operationalizing Deep Learning. Bachelor of Technology in Computer Science June 2022 MKSSS’s Cummins College of Engineering for Women, Pune, India. GPA: 3.8/4.0 SKILLS

Programming Languages: Java, Python, C++, C, SQL, JavaScript, HTML, CSS, TypeScript. Tools: Figma, TensorFlow, PyTorch, Scikit-learn, Keras, Explainable AI, LLMs, IDEs, Debuggers, Build Tools, Source Control. Technologies: React, Tailwind, Angular, AWS, GCP, Docker, Kubernetes, MySQL, MongoDB, CI/CD, Git, Agile Development. EXPERIENCE

Research Aide September 2024 - Present

Arizona State University, Tempe, AZ

• Designed a scalable LLM-based educational chatbot platform using React.js and Next.js, improving performance and load time efficiency by 25%.

• Integrated APIs and optimized workflows to reduce average response times, ensuring a seamless user experience. Software Engineer July 2022 - July 2023

PricewaterhouseCoopers (PwC), India

• Led Salesforce-SAP integration using MuleSoft, reducing data sync time by 40% and enhancing backend reliability.

• Designed modular UI components using JavaScript, CSS, and HTML, improving user experience and system efficiency.

• Collaborated on CI/CD pipelines to improve software quality and streamline deployment cycles. Software Engineer Intern May 2021 - July 2021

PricewaterhouseCoopers (PwC), India

• Developed secure and efficient business logic interfaces using Apex and JavaScript for real-time data workflows.

• Refactored legacy systems to optimize performance and reduce runtime complexities. Data Science Intern May 2020 - July 2020

Cloud Counselage Pvt. Ltd., India

• Built a machine learning pipeline achieving 95% accuracy through feature engineering and hyperparameter tuning.

• Enhanced prediction capabilities using Scikit-Learn for optimized decision-making. PROJECTS

SheDoesArt - E-commerce Website Present

• Developed a responsive React-based web application with TypeScript, Node.js,, improving code quality by 30%.

• Designed modular REST APIs for scalability and reduced page loading time through efficient data management. Sector-Based Trade Recommendation System Aug 2024

• Built a trade recommendation platform using Angular and MySQL, improving engagement by 30%

• Leveraged machine learning algorithms for accurate prediction models, enhancing decision-making system scalability, achieving a 20% boost in data retrieval speed.

Conversational AI Platform - NLP April 2022

• Developed a virtual banking assistant using NLP and MySQL, streamlining customer support.

• Implemented scalable backend services using Flask and BeautifulSoup, integrated with Telegram and WhatsApp. Carify - ML-based Web Application Jan 2022

• Developed Random Forest and Logistic Regression models to predict automobile maintenance needs with 92% accuracy.

• Conducted end-to-end data preprocessing and pipeline management, improving the model’s efficiency by 15%.

• Secured 2nd place among 50 teams and earned ”Certified Potential Real Venture” by Wadhwani Foundation. EXTRA-CURRICULARS

• Grader: CIS AWS, Data Visualization, and ABDA (ASU, Fall 2024).

• Research: Enhancing scRNA-Seq analysis for neurodegenerative diseases (Spring’2024) and Research Aide (Fall’2024).

• Recognition: Client Appreciation Award, PwC India (2023).

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