
Prashik Bhimte
ID: CCE290841

About Prashik Bhimte
As a final year Computer Science student at SGGS Nanded, I am driven by the challenge of building intelligent, end-to-end systems. I find deep satisfaction in taking a complex problem, architecting a data-driven solution, and seeing it come to life as a functional application. My journey into technology began with web development and has since focused on the real-world applications of Machine Learning. Through rigorous coursework at Bosscoder Academy and a recent internship, I have built a strong foundation in Python, Tebuale, Power BI, TensorFlow, and Scikit-learn. My experience in Edge AI was particularly formative. In this role, I successfully developed and deployed a real-time object detection model onto an ESP32 microcontroller using Embedded C. This project taught me not only about computer vision but also how to meticulously optimize for performance in resource-constrained environments—a skill I am eager to apply to new challenges. I am passionate about the entire project lifecycle. A model's true value is unlocked when it's accessible, which is why I've developed skills in building RESTful APIs with FastAPI and creating user-friendly interfaces with React.js. I am currently honing my skills in Deep Learning and NLP, with the goal of creating scalable, robust ML solutions that have a measurable impact. I am actively seeking 6-month internship roles for Spring 2026 (Jan-June) and full-time Machine Learning Engineer roles starting July 2026. I am keen to join a collaborative and innovative team that is solving challenging problems with data. If my profile aligns with your team's goals, let's connect!
Employment History
Suharsh Software Systems Pvt. Ltd. & Intentician TeaInvite company
22nd May 2025 to 19th Jul 2025
Software development intern
22nd May 2025 to 19th Jul 2025
Roles & Responsibility
Engineered real-time Edge AI Model Optimization using quantization techniques, achieving a 60%+ reduction in model size and significantly decreasing inference latency on low-power hardware. Developed a high-throughput, multi-threaded data pipeline (FreeRTOS, Embedded C) for real-time sensor acquisition and preprocessing, ensuring low-latency data readiness for on-device inference. Deployed and integrated Edge AI models (ESP-NN) for autonomous, on-device data inference, ensuring the model-to-hardware interface was stable for production use. Designed a full-stack visualization solution (React Native, BLE) for live monitoring and configuration of the deployed AI model outputs, improving user observability of the results.
Verification Pending
Education
B.Tech in Computer Science and Engineering
(Highest)Shir Guru Gobind Singhji Institute of Engineering and Technology, Vishnupuri, Nanded
17th Nov 2022 to 9th May 2026
Expertise
deep learning
4/5
Scikit-Learn
4/5
Seaborn
4/5
MatplotLib
4/5
Supervised Learning (Regression
4/5
Classification
4/5
Pandas
4/5
NumPy
4/5
FastAPI
4/5
Flask
4/5
Unsupervised Learning
4/5
Python
4/5
NLP (BERT
3/5
Recommender Systems
3/5
Time Series Analysis
3/5
SVM)
3/5
NLTK)
3/5
Exploratory Data Analysis (EDA)
3/5
Tensorflow
3/5
Linux (Ubuntu)
3/5
Git (Version Control)
3/5
VS Code
3/5
Github
3/5
JavaScript
3/5
SQL
3/5
power bi
2/5
Tableau
2/5
AWS (Basic)
2/5
Docker (basic)
2/5
C
2/5
