Aniket Mishra

AI Engineer

https://www.opentalent.in/aniket-mishra

AI Engineer with less than a year in Python, PyTorch, LLMs, and AI Engineering.

Key Strengths

Strong foundational understanding of deep learning architectures and their implementation from scratch (MLPs, Transformers, ViT, CLIP, LLaMA, PaliGemma).
Extensive practical experience in AI engineering, including RAG pipelines, agent workflows (LangGraph), visual grounding, and tool-based reasoning.
Proficiency in key AI/ML frameworks and tools such as PyTorch, TensorFlow, LangChain, FastAPI, and Docker.
Demonstrated ability to build end-to-end AI systems, from data preprocessing and model training to deployment and interpretability (e.g., FundusAI, CUA).
Proven problem-solving skills and innovation, evidenced by hackathon awards for AI-powered solutions.

Cultural & Operational Fit

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.

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About

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.

Top Skills

PythonPyTorchLlmsGitPlaywright

Projects

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.

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FundusAI

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.

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DeepLearning 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.

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CUA

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 Project

Certifications

1st 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

Key Strengths

Strong foundational understanding of deep learning architectures and their implementation from scratch (MLPs, Transformers, ViT, CLIP, LLaMA, PaliGemma).
Extensive practical experience in AI engineering, including RAG pipelines, agent workflows (LangGraph), visual grounding, and tool-based reasoning.
Proficiency in key AI/ML frameworks and tools such as PyTorch, TensorFlow, LangChain, FastAPI, and Docker.
Demonstrated ability to build end-to-end AI systems, from data preprocessing and model training to deployment and interpretability (e.g., FundusAI, CUA).
Proven problem-solving skills and innovation, evidenced by hackathon awards for AI-powered solutions.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Aniket Mishra

Key Strengths

Cultural & Operational Fit

About

Top Skills

Skills

Education

Projects

Certifications

Key Strengths

Cultural & Operational Fit