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    "name": "MUDDAM AKHILA",
    "summary": "Aspiring Software Engineer with a strong foundation in AI/ML, cloud technologies, and enterprise platforms, complemented\nby hands-on experience in Azure AI and ServiceNow. Adept at translating complex requirements into innovative, scalable,\nand value-driven solutions.",
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    {
      "company": "",
      "position": "ServiceNow Intern",
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        "Configured and streamlined workflow automation solutions within enterprise ServiceNow environments.",
        "Resolved platform configuration challenges through systematic analysis and cross-functional collaboration.",
        "Facilitated process optimization initiatives by translating operational requirements into automated workflows.",
        "Strengthened expertise in enterprise digital transformation and IT service management operations."
      ]
    },
    {
      "company": "Microsoft Initiative via Edunet Foundation (AICTE)",
      "position": "AI Azure Intern",
      "highlights": [
        "Engineered cloud-hosted AI solutions leveraging Microsoft Azure services and deployment frameworks.",
        "Orchestrated end-to-end model deployment workflows, translating analytical concepts into production-ready applications.",
        "Collaborated with technical mentors to troubleshoot deployment challenges and optimize solution performance.",
        "Leveraged cloud engineering practices to deliver scalable and reliable AI-driven services."
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  "education": [
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      "institution": "Malla Reddy Engineering College for Women Hyderabad",
      "degree": "Bachelor of Technology",
      "field": "Artificial Intelligence & Machine Learning",
      "startDate": "2022",
      "endDate": "2026",
      "score": "8.80/10"
    }
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    "Python",
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    "HTML5",
    "CSS3",
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    {
      "name": "Brain Tumor Detection System",
      "description": "Architected a convolutional neural network capable of accurately classifying brain tumor images. Engineered an image-preprocessing pipeline that enhanced prediction reliability and model consistency. Integrated a Flask-powered backend with a responsive web interface enabling real-time diagnostic predictions.",
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        "Flask",
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        "CSS"
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      "name": "Gender Voice Recognition System",
      "description": "Devised an intelligent voice-classification framework utilizing advanced audio feature extraction techniques. Architected a modular object-oriented codebase to improve maintainability and scalability. Implemented real-time inference services through Flask APIs, enabling efficient prediction delivery.",
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        "Python",
        "TensorFlow",
        "Flask"
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      "name": "Cisco PCAP – Programming Essentials in Python"
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    "highestEducation": "Bachelor's"
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