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Kishore Batchala

Machine Learning Engineer • k*****************@gmail.com • +91*******503 • drivetube.ai/•••••

Professional Summary

Machine Learning Engineer with 0 years of experience building machine learning models and full-stack prototypes. Strong foundation in Python-based ML (NumPy, Pandas, TensorFlow), experience implementing neural networks and Vision Transformer models, and practical web development skills using React and Node.js. Seeking an entry-level ML role to apply model development, data preprocessing, and end-to-end deployment skills.

Technical Skills

Programming Languages: Python,JavaScript,Java
Web Technologies: HTML,CSS,REST APIs
Frameworks and Libraries: React.js,Node.js,Express.js,NumPy,Pandas,TensorFlow,Keras,scikit-learn,Matplotlib
Databases: PostgreSQL,SQL
Data and Analytics: Deep Learning,Neural Networks,Computer Vision
Tools and Methodologies: Git,GitHub,VS Code,Jupyter Notebook

Work Experience

Coincent.ai
AI Intern (Vision Transformer)
2024 – 2024
AI internship focused on computer vision model development; implemented Vision Transformer architectures for image classification tasks and related data pipelines.
Tech Stack: Python, TensorFlow, NumPy, Git, GitHub
  • Implemented a Vision Transformer (ViT) architecture for image classification using Python and TensorFlow, translating model design into reproducible training code.
  • Designed and implemented image preprocessing and augmentation pipelines with NumPy and TensorFlow to boost dataset variety and model robustness.
  • Applied transfer learning and fine-tuning strategies to adapt pre-trained transformer components to domain-specific image data, reducing training time.
  • Built evaluation workflows measuring accuracy, precision, and recall; used these metrics to drive iterative model improvements and select best checkpoints.
  • Optimized training experiments via hyperparameter tuning and early stopping, improving convergence stability across runs.
  • Documented model design, training procedure, and reproducible scripts in Git repositories to support handover and future development.
Infosys Springboard
AI-ML Virtual Intern
2024 – 2024
Virtual internship program delivering practical AI/ML projects; worked on end-to-end machine learning workflows including data cleaning, model training, and evaluation.
Tech Stack: Python, Pandas, NumPy, scikit-learn, TensorFlow, Git, Jupyter Notebook
  • Developed end-to-end ML workflows in Python, performing data ingestion, cleaning, and exploratory analysis using Pandas and NumPy.
  • Engineered features and applied standardization and encoding techniques to prepare tabular and time-series inputs for model training.
  • Trained and validated models using scikit-learn and TensorFlow, implementing cross-validation and model selection to ensure generalization.
  • Carried out hyperparameter tuning and model evaluation with relevant metrics, iterating on model choices to meet project objectives.
  • Packaged experiments and notebooks with clear README and version control using Git to maintain reproducibility and traceability.
  • Delivered project reports summarizing methodology, results, and next steps for deployment or further research.

Projects

Human Stress Detection and Prediction Using ANN
Tools Used: Python, NumPy, Pandas, TensorFlow, Neural Networks
  • Built and trained an artificial neural network to predict human stress levels from physiological and behavioral datasets using TensorFlow.
  • Executed data preprocessing steps including cleaning, normalization, and feature selection to prepare multi-source input data.
  • Evaluated model performance using cross-validation and standard metrics; iteratively tuned architecture and hyperparameters to improve predictions.
  • Implemented reproducible experiment notebooks and version-controlled code on GitHub to document the research workflow.
Infosys Springboard AI Internship Project
Tools Used: Python, Pandas, scikit-learn, TensorFlow
  • Developed machine learning workflows including data cleaning, feature engineering, model training, and evaluation for real-world use cases.
  • Automated preprocessing and model evaluation pipelines to streamline experimentation and comparison of model variants.
  • Prepared detailed notebooks and summary reports to communicate findings and recommended next steps to stakeholders.

Education

Raghu Institute of Technology
B.Tech in Computer Science (AI/ML) • 2022 – 2026
Sri Prakash Junior College
Intermediate (MPC) • 2020 – 2022
Sri Prakash Vidya Niketan
SSC • 2020

Certifications

Python — HarvardX
Generative AI — Infosys
AI Primer — Infosys
Responsive Web Design — freeCodeCamp
Problem Solving in C — NPTEL
Programming in Java — NPTEL

Achievements

  • Active hackathon and technical competition participant: Participated in multiple hackathons and technical competitions to develop practical solutions under time constraints.
  • Community contributor to sustainability initiatives: Contributed to community initiatives focused on sustainability by applying technical skills to local projects.

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