BOMMINENI CHANDRA SEKHAR
AI/ML Engineer • c*****************@gmail.com • +91*******036 • drivetube.ai/•••••
Professional Summary
AI/ML Engineer with 0 years of experience building machine learning pipelines, computer vision models, and data engineering solutions through academic projects and virtual internships.
Technical Skills
Programming Languages: Python,Java
Web Technologies: HTML
Frameworks and Libraries: TensorFlow,PyTorch,scikit-learn,NumPy,Pandas,OpenCV,Matplotlib
Databases: SQL,Data Modeling,Relational Databases,Data Validation
Cloud and DevOps: AWS,AWS SageMaker,AWS S3,Linux
Data and Analytics: ETL,Power BI
Tools and Methodologies: Git,MS Word
Networking & Infrastructure: Juniper Networking,Network Topology Design,Network Protocol Troubleshooting
Work Experience
Juniper Networks | EduSkills Foundation
Networking Cloud Virtual Intern
April 2025 – June 2025
Worked on cloud networking simulations and virtual network topologies as part of Juniper Networks EduSkills, supporting cloud deployment and protocol troubleshooting.
Tech Stack: Juniper Networks tools, Virtual network simulators, Python, Git, MS Word
- Engineered scalable cloud network topologies using virtualized tools and reusable templates, improving deployment efficiency by 15% through standardized designs.
- Collaborated with a cross-functional team of 5 to diagnose and resolve network protocol failures during simulations, achieving a 95% resolution rate for connectivity issues.
- Developed Python automation scripts to validate connectivity and failover scenarios, cutting manual test cycles by approximately 40%.
- Performed performance tuning of virtual network elements to reduce simulated latency and improve throughput across cloud testbeds.
- Maintained rigorous technical documentation and runbooks for cloud infrastructure setup using MS Word to ensure reproducibility and knowledge transfer.
- Implemented version control and change-tracking for network configurations using Git to support rollback and iterative topology refinement.
AWS Academy | EduSkills Foundation
AWS AI & ML Virtual Intern
September 2024 – December 2024
Built and optimized machine learning pipelines and computer vision models in AWS Academy assignments, focusing on model performance and stakeholder reporting.
Tech Stack: AWS, AWS SageMaker, TensorFlow, OpenCV, Power BI, Python
- Architected end-to-end ML pipelines on AWS to streamline data preprocessing, training, and evaluation, reducing average processing time by 20% through parallelization and optimized workflows.
- Implemented computer vision models using TensorFlow and OpenCV, achieving 92% accuracy on automated image classification tasks via tailored architectures and augmentation.
- Conducted hyperparameter tuning and model optimization to improve inference speed while maintaining model accuracy for production-like workloads.
- Packaged reproducible training and evaluation workflows using AWS SageMaker to support scalable training runs and simplified model management.
- Developed automated performance dashboards and stakeholder reports in Power BI to visualize model metrics, error analysis, and deployment readiness.
- Collaborated on dataset labeling, augmentation strategies, and validation pipelines to expand training samples and reduce class imbalance.
AWS Academy | EduSkills Foundation
Data Engineering Virtual Intern
April 2024 – June 2024
Supported data engineering tasks inside AWS Academy exercises focused on large-scale dataset processing, validation, and schema design for analytics.
Tech Stack: Python, SQL, ETL, Data Modeling, Power BI, AWS
- Streamlined data ingestion and extraction workflows with Python automation, saving approximately 30 hours of manual effort per month for the management team.
- Implemented data quality checks and validation logic for datasets exceeding 1,000,000 records, ensuring a 99.9% dataset integrity rate.
- Designed and normalized complex data schemas to improve query performance and retrieval speeds within enterprise-style databases.
- Built ETL pipelines with staged processing and incremental loads to reduce processing windows and improve reliability of downstream analytics.
- Created SQL reports and Power BI visualizations to summarize data health, trends, and anomalies for stakeholders and decision makers.
- Documented data workflows and added unit tests for transformation functions to increase reproducibility and reduce regression defects.
Education
Chalapathi Institute of Technology
Bachelor of Technology in Artificial Intelligence & Machine Learning • Expected May 2026
Sri Chaitanya Junior College
Intermediate (MPC) • April 2022
Z.P. High School
Secondary School Certificate (SSC) • April 2020
Certifications
Networking Cloud — Juniper Networks | EduSkills
Python Foundation — Infosys Springboard
AWS AI & ML — AWS Academy | EduSkills
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