AI/ML Engineer

Hello, I am Deepak Singh

B.Tech CSE (2026) Graduate & AI Engineer specializing in LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and production machine learning systems.

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01 — About

Deepak Singh
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Tech Stack
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Key Projects
Degrees
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Best Time

I'm a B.Tech CSE (2026) graduate and AI Engineer who builds LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and production-grade machine learning systems.

I design end-to-end AI solutions: scalable backend APIs, MLOps workflows with Docker, MLflow and CI/CD, and cloud deployments, using Python, FastAPI and Flask. My foundation spans machine learning, deep learning and software engineering, and I have a track record of shipping deployable AI products, including Kaggle competition work.

Deepak Singh
0
Tech Stack
0
Key Projects
2
Degrees
0
Best Time
Hover / tap to flip ↻
🛡️
AI Engineer Intern
CyCrew
Oct 2025 – Jan 2026
  • Built an AI-powered SIEM incident analysis platform using LLMs and Retrieval-Augmented Generation (RAG), enabling automated alert investigation and structured, LLM-generated incident response reports for Security Operations Center (SOC) teams.
  • Designed a full-stack AI pipeline (FAISS vector search, FastAPI backend, n8n workflow orchestration, Vue.js frontend) that reduced manual triage effort and accelerated SOC decision-making.
  • Engineered retrieval and prompting strategies to ground LLM outputs in security alert context, improving the accuracy and consistency of automated incident analysis.
RAG / LLMs FAISS FastAPI n8n
⚡ Quick Summary
AI Engineer Intern · CyCrew
  • Automated SOC alert triage with an LLM + RAG pipeline
  • Owned the stack end to end: FAISS, FastAPI, n8n, Vue.js
  • Cut manual investigation effort and sped up incident decisions
  • Grounded LLM answers in alert context for consistent reports
Flip back ↻
🤖

LLMs & Generative AI

Building grounded, retrieval-powered AI products.

LLM AppsRAGFAISSEmbedding ModelsPrompt EngineeringAgentic Workflows
📊

Machine Learning & Data Science

From messy data to evaluated, tuned models.

Scikit-learnTensorFlowXGBoostPandasNumPyFeature EngineeringModel Evaluation
⚙️

Backend & APIs

Fast, clean services that ship models to users.

PythonJavaSQLFastAPIFlaskREST APIsn8n
🚀

MLOps & DevOps

Reproducible pipelines, CI/CD and cloud deploys.

GitDockerJenkins CI/CDMLflowGoogle Cloud (GCP)
04 — Projects

Featured Projects

Click “Read details” on any project to see the full description

PROJECT / 01
📅 Jun 2025 – Aug 2025
Hotel Reservation Prediction
Hotel Reservation Prediction
End-to-end ML + MLOps pipeline predicting hotel booking cancellations, from GCS ingestion to Jenkins CI/CD deployment on GCP.
MLflowDocker / GCPJenkins
GitHub →
PROJECT / 02
📅 May 2025 – Jun 2025
Virtual Data Analyst Agent
Virtual Data Analyst Agent
AI-powered API that uses LLMs to automatically source, prepare, analyze and visualize data, with a self-correcting code loop.
LLM AgentAPI
GitHub →
PROJECT / 03
📅 Jan 2026 – Feb 2026
Legal Document Classification — Kaggle
Legal Document Classification — Kaggle
Classified legal documents into 30 classes by fine-tuning a transformer with LoRA, training only ~0.8% of the parameters.
LoRA / PEFTTransformers
PROJECT / 04
📅 Mar 2025 – Apr 2025
Virtual Teaching Assistant
Virtual Teaching Assistant
RAG-powered API that answers student queries from course and forum content, with reference links, in under 30 seconds.
RAGEmbeddings
GitHub →
PROJECT / 05
📅 Feb 2026 – Mar 2026
Engage2Value — Kaggle Competition
Engage2Value — Kaggle Competition
Predicted customer purchase value from multi-session behavior. R² 0.6813, rank 152 of 1500 teams (top 10%).
XGBoostFeature Engineering
GitHub →
PROJECT / 06
📅 Sep 2025 – Nov 2025
Household Services Management
Household Services Management
Full-stack platform connecting households with service providers for booking, scheduling and management.
Flask + VueRedis / Celery
GitHub →
Tap to flip ↻
🎓
B.Tech, Computer Science and Engineering
Dronacharya College of Engineering, Gurgaon
Jun 2022 – Jul 2026
📘 Summary
Dronacharya College of Engineering, Gurgaon
  • Core CS: data structures, algorithms, DBMS, operating systems, networks
  • Specialised on my own in AI/ML, LLMs and RAG systems
  • Shipped real projects, an industry internship and Kaggle results alongside coursework
Tap to flip ↻
🎓
BS in Data Science and Applications
Indian Institute of Technology (IIT), Madras
Sep 2022 – Sep 2026
📘 Summary
Indian Institute of Technology (IIT), Madras
  • Online degree focused on statistics, programming and machine learning
  • Hands-on with data analysis, modelling and application development
  • Studied in parallel with my B.Tech
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📜
Supervised Machine Learning: Regression and Classification
DeepLearning.AI / Stanford University
🧠 Skills I Gained
  • Linear & logistic regression
  • Gradient descent
  • Regularization
  • Scikit-learn / NumPy
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📜
Advanced Learning Algorithms
DeepLearning.AI / Stanford University
🧠 Skills I Gained
  • Neural networks (TensorFlow)
  • Decision trees & ensembles
  • XGBoost
  • Bias / variance tuning
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⚡
FastAPI
Udemy
Issued Jun 2026
🧠 Skills I Gained
  • REST API design
  • Pydantic validation
  • Async endpoints
  • Dependency injection
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☁️
Applied Skills: NLP Solution with Azure AI Language
Microsoft
🧠 Skills I Gained
  • Text classification
  • Entity recognition
  • Summarization
  • Question answering

Looking for an AI/ML Engineer? Reach out on any of these.

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© 2026 Deepak Singh · Built with curiosity & a Rubik's cube