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Bindu Chandra Shekar Reddy

Software Engineer • Sacramento, CA • b**********@gmail.com • +12******362 • drivetube.ai/•••••

Professional Summary

Software Engineer with 0 years of experience in software development, testing, and full-stack application development. Experienced with Java, Python, JavaScript, React, REST APIs, cloud and container platforms, and end-to-end ML pipelines. Seeking software validation, full-stack engineering, or ML engineering roles where I can apply SDLC discipline, testing expertise, and cross-functional collaboration to deliver reliable systems.

Technical Skills

Programming Languages: Java,Python,JavaScript,C,PHP
Web Technologies: REST APIs
Frameworks and Libraries: React,Node.js,Spring Boot,Scikit-learn,TensorFlow,PyTorch,NumPy,Pandas,Matplotlib
Databases: SQL,MySQL
Cloud and DevOps: AWS,Docker,Kubernetes,Google Kubernetes Engine
Data and Analytics: XGBoost
Tools and Methodologies: Git,VS Code,Google Colab,Xcode,SDLC,Agile,Testing & Validation,Debugging,Technical Documentation,Code Review
ML Models & Techniques: Convolutional Neural Networks,Artificial Neural Networks,Transformers,Transfer Learning

Work Experience

California State University, Sacramento
Sacramento, CA
Instructional Student Assistant
Jan 2025 – May 2026
Worked in an academic computer science program supporting courses and laboratory instruction for undergraduate programming and software engineering assignments.
Tech Stack: Java, Git, VS Code, Unit testing concepts
  • Tutored students on object-oriented programming concepts and Java fundamentals to improve comprehension of course assignments and core CS topics.
  • Guided students through debugging, unit testing, and validation processes, teaching test design and root-cause analysis techniques.
  • Reviewed student code for functionality, maintainability, and style; provided constructive feedback to raise code quality and learning outcomes.
  • Maintained and distributed lab materials and sample projects using Git and VS Code to standardize development environments for course sections.
  • Co-developed and updated assignment instructions and grading rubrics to clarify requirements and reduce common submission errors.
  • Supported faculty with evaluation of student submissions and offered remediation strategies for recurring technical issues.
Teleindia Networks Pvt. Ltd
Bengaluru, India
Web Developer
Jun 2023 – Jul 2024
Contributed to full-stack web application development and backend services for the company's web platforms, collaborating with product and design teams to deliver business-aligned features.
Tech Stack: React, Node.js, PHP, MySQL, REST APIs, Docker, Kubernetes, AWS, Git
  • Built and maintained full-stack web applications using React, PHP, Node.js and MySQL following SDLC practices to deliver user-facing features and internal tools.
  • Developed and integrated RESTful APIs and optimized backend logic, reducing average response times by 30% through query and endpoint improvements.
  • Implemented application testing and debugging workflows, identified defects, and resolved production issues to improve reliability and user experience.
  • Supported containerized deployments and monitoring using Docker, Kubernetes and AWS, contributing to platform stability and faster incident response.
  • Collaborated with product managers, designers, and engineers to gather requirements, produce technical specifications, and prioritize deliverables.
  • Authored technical documentation for APIs, system components, and release notes to streamline handoffs and onboarding for new developers.
Nanorobotics Embed Technologies
Bengaluru, India
Machine Learning Intern
Sep 2021 – Oct 2021
Worked with an embedded robotics engineering team to develop machine learning models and inference pipelines for on-device analytics and robotics applications.
Tech Stack: Python, NumPy, Pandas, Matplotlib, ANN, Embedded inference pipelines, Git
  • Developed and evaluated ANN models in Python using NumPy and Pandas to produce reliable predictive outputs for embedded analytics tasks.
  • Built ML inference pipelines for embedded devices, implementing preprocessing, model loading, and runtime inference to enable real-time analytics.
  • Optimized model artifacts for edge deployment by reducing memory footprint and improving inference latency for constrained hardware.
  • Integrated Python-based modules with embedded software workflows and validated model outputs against sensor inputs to ensure correctness.
  • Documented experimental setups, validation results, and model performance trade-offs to inform engineering design decisions.
  • Presented findings and recommended ML integration approaches to the engineering team to support roadmap planning and prototype development.

Projects

NeuroFusionGPT – Multimodal Stress Detection System | Jul 2025 – May 2026
Tools Used: Python, EEG, ECG data processing, Feature extraction, TensorFlow, Model evaluation
  • Designed and implemented a multimodal system to detect physiological stress using EEG and ECG datasets with end-to-end preprocessing and inference.
  • Built ML pipeline including signal preprocessing, feature engineering, model training, and evaluation using accuracy, precision, recall, F1-score and confusion matrix.
  • Implemented personalized recommendation logic to provide AI-driven wellness suggestions based on predicted stress levels and model confidence.
  • Validated model performance on held-out datasets and iterated on features and architectures to improve robustness.
XML Transformation and Validation System | Feb 2026 – May 2026
Tools Used: XSLT, XML validation, Debugging, Version control
  • Contributed to development and validation of XSLT transformations for XML-based data processing workflows to ensure correct output formats.
  • Implemented and tested XSLT generation components and validation logic to verify compliance with project requirements.
  • Performed debugging and validation testing to identify transformation edge cases and ensure stability across datasets.
  • Documented transformation logic, testing procedures, and validation results to support maintainability and future enhancements.
IoT-Based Health Monitoring System with Edge Computing | Jan 2025 – May 2025
Tools Used: iOS development, Edge computing, AWS, Docker, Kubernetes
  • Developed an iOS application to visualize real-time wearable IoT sensor data for health monitoring and anomaly detection.
  • Implemented edge computing components to enable low-latency preprocessing and initial anomaly detection on-device.
  • Integrated cloud backend services on AWS and containerized services using Docker and Kubernetes for scalable data ingestion.
  • Conducted end-to-end testing and validation of data flows, ensuring secure and reliable communication between device, edge, and cloud.
ML-based Medical Diagnostics for Infectious Diseases | Aug 2025 – Dec 2025
Tools Used: XGBoost, Feature engineering, Data preprocessing, Model evaluation
  • Developed a supervised ML pipeline using epidemiological data (263K+ samples) to predict COVID-19 risk and prioritize high-risk cases.
  • Engineered clinical and temporal features such as comorbidity counts and symptom-to-admission intervals to improve model signal.
  • Built and tuned an XGBoost model achieving 0.80 ROC-AUC and 0.73 recall for high-risk case detection on validation data.
  • Designed robust preprocessing to handle noisy, imbalanced healthcare data and documented model limitations and deployment considerations.
Plant Leaf Disease Detection Using CNN | Aug 2021 – Jun 2022
Tools Used: Transfer learning, VGG16, ResNet50, Python
  • Built a deep learning-based disease detection pipeline using transfer learning with VGG16 and ResNet50 to classify plant leaf diseases.
  • Achieved ~95% classification accuracy through data augmentation, preprocessing, and architecture selection.
  • Implemented preprocessing and visualization pipelines to analyze model predictions and support real-time classification scenarios.
  • Packaged model artifacts and documented inference workflows for potential agricultural deployment.

Education

California State University, Sacramento
Master of Science, Computer Science • Sacramento, CA • Aug 2024 – May 2026
KNS Institute of Technology (VTU)
Bachelor of Engineering, Computer Science and Engineering • Bengaluru, India • Aug 2018 – Jun 2022

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