Vimal Kumar

About

Machine Learning Engineer with hands-on experience building production ML systems, GenAI applications, and deep learning pipelines. Experience includes internships and project work across real-time fraud detection, enterprise RAG, and predictive modeling with measurable performance impact.

Experience

• Data Science & ML Project-Based Intern
  UpSkill Campus & Uniconverge Technologies (UCT)
  Mar 2026 – Apr 2026

  ▸ Built an end-to-end RUL prediction pipeline on the NASA CMAPSS dataset (FD001–FD004) using a 2-layer LSTM model with Dropout regularization and EarlyStopping, achieving significant RMSE improvement over a Random Forest baseline. ▸ Engineered rolling window features (mean, std over 10-cycle windows) and applied piecewise linear RUL labeling (cap=125 cycles) to prepare multivariate time-series sensor data for deep learning. ▸ Developed a silica impurity prediction model for a real industrial flotation plant dataset using XGBoost with GridSearchCV hyperparameter tuning, achieving strong R² scores on both standard and iron-feature-excluded variants. ▸ Delivered complete project reports and

• Machine Learning Intern
  Unified Mentor Private Limited
  Jun 2025 – Jul 2025

  ▸ Developed and evaluated ML models on 5,000+ clinical records for liver cirrhosis staging, achieving 92% diagnostic accuracy and supporting datadriven clinical insights. ▸ Built and validated a vehicle price prediction model achieving ₹60K MAE using XGBoost and Optuna hyperparameter tuning on real-world automotive datasets. ▸ Improved model performance by 15% through systematic feature engineering, stratified cross-validation, and structured experimentation workflows. ▸ Established ML best practices across the team including Git-based versioning, reproducible training pipelines, and deployment-ready model packaging.

Education

• B.Tech
  Rajkiya Engineering College
  Computer Science & Engineering · Nov 2020 – Jul 2024
• 12th / Higher Secondary (Class 12)
  shree radha krishana inter college · up board
  2016 – 2017
• 10th / Secondary (Class 10)
  shree radha krishana inter college · up board
  2014 – 2015

Skills

• SQL
• FastAPI
• Git
• Python
• Linux
• NumPy
• Pandas
• scikit-learn
• TensorFlow
• AWS
• Docker
• Keras
• Grafana
• REST APIs
• RAG
• Kafka
• LLMs
• XGBoost
• Prometheus
• MLflow
• Isolation Forest
• Shap
• Evidentlyai

Projects

• AI Talent Intelligence Platform ↗
  Scikit-learn, XGBoost, LangChain, FAISS, FastAPI, MLflow, Streamlit, HuggingFace

  AI recruiter tool for resume ranking, scoring, matching, resume Q&A, and semantic candidate search.

• Enterprise RAG Intelligence System ↗
  Python, NumPy, FastAPI, Streamlit, Docker, Claude API, RBAC, MMR Reranking

  Production RAG pipeline with hybrid retrieval, MMR reranking, RBAC, evaluation framework, FastAPI API, and Streamlit UI.

• Real-Time Fraud Detection ML Platform ↗
  Apache Kafka, FastAPI, MLflow, Docker, Prometheus, Grafana, Isolation Forest

  Kafka-based streaming ML system for fraud predictions with sub-200ms latency, MLOps pipeline, observability stack, and Isolation Forest anomaly detection.

Courses & certifications

• Data Science & Machine Learning Internship · UpSkill Campus & UCT · 2026
• Data Science Master Class – End-to-End ML using Python · Udemy · 2024
• Machine Learning – From Basics to Advanced · Udemy · 2024

🗣️ Languages

• english · Fluent
• hindi