Meruva Lokesh
Building Production-Ready ML Systems | Computer Vision & NLP | 87% Accuracy ResNet50 Deployed | Seeking ML/MLOps Internship Mar–Jun 2026
- Role
- Nlp Engineer (Project) at Personal Projects
- Location
- Vijayawada, AP, IN
- LinkedIn followers
- 500 followers
About Meruva Lokesh
I\'m a Computer Science student at KL University passionate about building machine learning systems that actually work in production.What I DoI specialize in end-to-end ML development—from data preprocessing and model training to deployment and API design. My work focuses on Computer Vision and Natural Language Processing, with recent projects including a ResNet50 vehicle classifier (87% accuracy), an NLP resume analyzer deployed on Hugging Face, and a handwritten digit recognizer with Flask integration.What Drives MeThe gap between \"model works in development\" and \"model works in production\" fascinates me. Through building and deploying my own projects, I\'ve wrestled with real challenges: model optimization, API error handling, inference speed, and deployment architecture. This hands-on experience has given me deep respect for platforms that make ML deployment seamless.Technical SkillsPython • TensorFlow • Keras • Flask • Gradio • scikit-learn • Computer Vision • NLP • Model Deployment • API Development • ResNet • CNNWhat I\'m Looking ForA 3-4 month ML Engineering or MLOps internship (March-June 2026) where I can contribute to production ML systems before transitioning to my full-time role in July. I\'m particularly interested in teams working on model deployment, ML infrastructure, or AI product development.I\'m remote-first, offer full-time commitment, and bring a portfolio of deployed projects. Let\'s connect if you\'re building production ML systems or have opportunities that match!
Experience
Nlp Engineer (Project)
Mar 2025 — Present
NLP Resume AnalyzerDeployed on Hugging Face Spaces using Gradio: Goal: Help job seekers optimize resumes using NLP techniques Implementation- Built NLP pipeline for text extraction and keyword matching- Implemented scoring logic based on job descriptions- Deployed on Hugging Face Spaces using Gradio- Created interactive UI for real-time feedback Impact: 500+ resumes analyzed, 85% keyword matching accuracyTech Stack: Python, NLP, scikit-learn, Gradio, Hugging Face SpacesDeploying on Hugging Face Spaces was my first experience with managed ML hosting—it made deployment 10x easier than my Flask setup.
Education
KL University
Bachelor of Technology - BTech, Computer Science
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