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AI Engineer with less than a year in Python, PyTorch, LLMs, and AI Engineering.
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Aniket Mishra is a highly motivated Junior AI Engineer currently pursuing a B.Tech in Artificial Intelligence and Data Science. With a strong foundation in Python, PyTorch, and various AI/ML frameworks, Aniket has successfully developed and deployed several impactful projects. These include a browser automation agent, a healthcare AI system for retinal disease screening, and a document-centric question answering system, demonstrating practical skills in AI Engineering, machine learning, and system integration with tools like Docker and FastAPI.
College of Technology and Engineering
B.Tech · Artificial Intelligence and Data Science
September 1, 2023 – January 1, 2027
Knexion
September 1, 2023 – June 1, 2026
Built a document-centric question answering system that converts PDFs into a structured knowledge base using entity extraction and semantic embeddings. Implemented a hybrid retrieval pipeline combining vector similarity search and knowledge graph traversal for multi-document reasoning. Developed a LangGraph-based agent workflow for retrieval, routing, answer generation, and fallback web search with interactive visualization support.
View ProjectFundusAI
September 1, 2023 – June 1, 2026
Developed a healthcare AI system for automated retinal disease screening using deep learning on fundus images, classifying AMD, Cataract, Diabetic Retinopathy, and Normal categories. Fine-tuned an EfficientNet-B3 model on the AMDNet23 dataset with augmentation and preprocessing techniques, achieving 98% test accuracy and 0.98 Macro F1-score. Integrated Grad-CAM interpretability visualizations and deployed the application using FastAPI and Docker for reproducible inference workflows.
View ProjectDeepLearning From Scratch
September 1, 2023 – June 1, 2026
Re-implemented foundational and modern deep learning architectures from first principles to develop a deeper understanding of neural network internals and training dynamics. Built models including MLPs, Transformers, Vision Transformers (ViT), CLIP, LLaMA, and PaliGemma, implementing components such as self-attention, positional encoding, multimodal embeddings, and decoder-only language modeling. Developed end-to-end training pipelines covering data preprocessing, model implementation, training loops, evaluation, and inference with minimal reliance on high-level abstractions.
View ProjectCUA
September 1, 2023 – June 1, 2026
Built a computer-use agent capable of autonomously interacting with browser environments using screenshots, UI grounding, and tool-based reasoning. Implemented a two-stage visual grounding pipeline using OmniParser and set-of-mark prompting for reliable localization and interaction with UI elements. Developed a sandboxed execution environment using Playwright and Docker with integrated tracing and observability for debugging agent behavior and tool execution.
View Project1st Place - Hackitup 2.0 Hackathon (CTAE Udaipur)
CTAE Udaipur
June 1, 2026 – Present
2nd Place Visionary AI Hackathon (C-DAC Delhi)
C-DAC Delhi
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a diverse range of AI applications, from healthcare diagnostics to document Q&A and autonomous agents, indicating adaptability and a broad interest in AI challenges. The focus on building systems from scratch and winning hackathons suggests a proactive, innovative, and competitive spirit, which aligns well with a dynamic AI engineering environment. The candidate is currently pursuing a B.Tech, indicating a strong academic foundation and a continuous learning mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong drive for understanding complex systems from first principles and a practical, hands-on approach to problem-solving. Participation in hackathons suggests teamwork and rapid prototyping abilities. The detailed project descriptions demonstrate good technical communication.