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AI Engineer with less than a year in Deep Learning & Computer Vision.
AI Engineer with deep expertise in deep learning, computer vision, and end-to-end ML pipeline development with hands-on experience building production-grade CNN architectures, medical imaging AI systems, and real-time computer vision applications. Proficient in TensorFlow, Keras, OpenCV, and scikit-learn with strong foundations in transfer learning, data augmentation, and model optimization for resource-constrained environments. Proven track record of shipping CV-powered products spanning healthcare diagnostics, IoT security surveillance, and edge-AI deployment. Experienced in MLOps workflows, model evaluation frameworks, and bridging research-grade accuracy with real-world inference latency constraints. Strong Python programming skills with additional experience in LLM integration and full-stack AI product development. Open to opportunities in Computer Vision Engineering, Deep Learning, MLOps, and AI/ML Engineering.
Chhatrapati Shivaji Maharaj University, Panvel
B.Tech · Computer Science
N/A – June 30, 2023
KLE Society's Lingaraj College, Belgaum
Higher Secondary · Computer Science
N/A – May 31, 2022
GirlScript Summer of Code (GSSOC)
AI & Agents Contributor
May 1, 2026 – Present
India
Rochester Institute of Technology
Prompt Engineering Research Intern
May 1, 2026 – Present
India
Quantium
Software Engineer Intern
April 1, 2026 – April 1, 2026
India
NCP No Code Productions
Co-Founder
February 1, 2026 – Present
India
NaukriEase.Org
Operation Executive
June 1, 2024 – December 1, 2024
India
Pneumonia-CNN
June 5, 2026 – Present
Architected a production-grade CNN pipeline using TensorFlow/Keras with transfer learning (ImageNet pre-trained weights) and advanced data augmentation (rotation, zoom, flip, brightness) to achieve high classification accuracy on medical imaging datasets. Implemented robust preprocessing pipelines (normalization, resizing, class balancing via SMOTE) and clinical-grade evaluation metrics (precision, recall, F1-score, AUC-ROC, confusion matrices) for reliable diagnostic support. Deployed a modular, reproducible training workflow with experiment tracking, model checkpointing, early stopping, and performance visualization suitable for healthcare AI research and production deployment.
View ProjectAI-Powered Network Security Sentinel
June 5, 2026 – Present
Engineered a hardware-software integrated security system using NodeMCU (ESP8266) in promiscuous mode to sniff 802.11 network packets, paired with Isolation Forest for real-time anomaly detection on non-linear signal metadata. Designed a high-speed Python serial bridge achieving sub-second latency telemetry ingestion, and built a Streamlit SOC dashboard with live data visualizations, threat heatmaps, and automated alerting. Demonstrated edge-AI deployment capabilities by bridging embedded systems with cloud-based ML inference, showcasing system-level thinking across hardware, firmware, and AI software layers.
View ProjectFine-Tuned Medical QA LLM (Llama-3.1-8B)
June 5, 2026 – Present
Fine-tuned Meta's Llama-3.1-8B-Instruct on PubMedQA using QLORA (r=16, 4-bit quantization) on a single Colab T4 GPU, achieving 89 exact-match accuracy (up from 62 base model) with 22 minute training time and 75% memory reduction vs. full fine-tuning. Implemented domain-specific instruction templates with strict context binding to minimize hallucination, and published LoRA adapters to HuggingFace Hub under Apache-2.0 license. Deployed dual inference pipelines: a Streamlit web interface for interactive medical QA, and an Ollama GGUF endpoint for local, privacy-preserving inference on consumer hardware.
View ProjectPromptGit
June 5, 2026 – Present
Built a CLI tool using TypeScript that parses repository structure, extracts code semantics via AST analysis, and generates optimized prompts for "vibe coding" and AI agent workflows. Implemented intelligent prompt generation algorithms that preserve architectural intent, dependency context, and coding conventions to maximize AI agent code generation accuracy.
View ProjectAI Impact Summit Buildathon
HCL GUVI
March 1, 2026 – Present
Git & GitHub Bootcamp
LetsUpgrade
September 1, 2025 – Present
Oracle Cloud Infrastructure 2025 Certified AI Foundations Associate
Oracle
August 1, 2025 – Present
Deloitte Australia Data Analytics Job Simulation
Forage
August 1, 2025 – Present
IBM AI Foundations
IBM
March 1, 2025 – Present
Tata Group Data Visualisation Job Simulation
Forage
June 1, 2024 – Present
Cultural Fit Analysis
The candidate's involvement in open-source contributions (GSSOC), personal projects, and a co-founder role indicates a proactive, self-driven individual with a strong passion for AI and technology. The diversity of projects, from medical AI to IoT security and prompt engineering tools, showcases a broad interest and adaptability, which aligns well with dynamic, innovative environments. Their experience with remote and hybrid work models suggests flexibility and self-management. The focus on deployable, production-ready solutions and architectural discussions aligns with a culture that values practical impact and robust engineering.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project architectures (e.g., hardware-software integration for network security). Their experience as a Co-Founder and contributor to GSSOC suggests initiative, collaboration, and an ability to lead and contribute to end-to-end project lifecycles. The 'Operation Executive' role, though not technical, indicates experience in streamlining processes and coordinating workflows, which are valuable for operational efficiency in an engineering role. The resume highlights a focus on measurable improvements and robust performance, indicating a results-oriented approach.