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Vijay Vishwakarma
Looking for a jobAI Engineering Intern
I build deployable AI systems, from forecasting pipelines to LLM agents and recommendation engines.
IndiaAI Engineering Intern at Edunet Foundation
About
I've built deployable AI solutions through internships at Edunet Foundation and YBI Foundation, including a carbon-emission forecasting pipeline that achieved 93.3% prediction accuracy and a hybrid music recommendation system that improved precision by 23.4% over simpler models.
I'm most aligned with AI and data engineering, using PyTorch, LangChain, Scikit-Learn, Python, cloud services, and containerized deployment. My projects include a DeepSeek-R1 consensus agent designed to reduce hallucinations, a voice translation and cloning utility, and a CNN-RNN DNA sequence classifier that outperformed a baseline by 24%.
Experience
AI Engineering Intern
Engineered a Carbon Emission forecasting ML pipeline using Python, Scikit-Learn and Airflow, achieving a 93.3% prediction accuracy score on a noisy 35-year historical sensor dataset. Streamlined data processing and hyper-parameter tuning via MLflow, and deployed the containerised project using Docker.
Pythonscikit learnAirflowMLFlowDocker
AI Engineering Intern
Transformed data into analytical insights using statistics and probability via NumPy and Matplotlib for data visualization. Developed a hybrid music recommendation system combining collaborative filtering with NLP, resulting in higher precision by 23.4% than simpler models, and deployed the pipeline at client side.
NumPyMatplotlibNLPCollaborative FilteringRecommendation Systems
Education
Chhatrapati Shahu Ji Maharaj University
Pursuing a Bachelor of Technology in Computer Science & Engineering with an AI specialization, maintaining a CGPA of 8.46/10.00.