cv

My comprehensive curriculum vitae highlighting my experience in AI/ML, research work, and technical achievements.

Basics

Name Narasimha Karthik J
Label Applied Scientist | ML Engineer | Applied ML Engineer | Aspiring Research Scientist
Email narasimhajwalapuram2026@u.northwestern.edu
Url https://JNK234.github.io
Summary MS in AI at Northwestern University | Applied Science Intern at Relativity | Ex-Boeing Data Scientist | Building intelligent systems with focus on LLMs, NLP, and Reinforcement Learning

Work

  • Sep 2024 - Present
    Research Assistant
    CCL Lab - Northwestern University
    Developing frameworks for code generation using genetic programming with state-of-the-art LLMs including Grok, Claude, and DeepSeek models.
    • Developing genetic programming frameworks with LLMs
    • Building verification and performance tracking systems
    • Working with LangChain and LangGraph libraries
  • Jun 2025 - Aug 2025
    Applied Science Intern
    Relativity
    Led cross-functional AI initiatives to automate legal document review processes, working with Product, UX, and Engineering teams.
    • Led cross-functional initiative reducing document review time by 60%
    • Built insights extraction pipeline with 87.5% accuracy processing 46,864 legal documents
    • Created 600+ document benchmark dataset improving model coverage from 60% to 95%
    • Achieved 40% cost reduction through tiered GPT-4o/mini processing strategy
    • Implemented scalable Databricks labeling system with 95% inter-rater agreement
  • Jul 2022 - Aug 2024
    Data Scientist
    The Boeing Company
    Developed AI-driven solutions for aircraft maintenance and cost prediction, working in the Research and Operations wing of Boeing Commercial Airplanes division.
    • Secured $200k funding through AI-driven document automation demonstration
    • Trained and fine-tuned GPT-2, Llama models on Aircraft Maintenance Manuals using PEFT techniques
    • Implemented RAG system reducing manual effort by 80%
    • Developed dynamic cost prediction models with 2M+ rows of data achieving R-score of 0.9
    • Led hiring process for ML Engineers, onboarding 6 candidates from 50 applicants
  • Jul 2021 - Jun 2022
    Software Engineering Intern
    Invento Robotics
    Developed iOS applications and AI-powered robotics solutions including fleet management and human fall detection systems.
    • Developed 'Invento Fleet' iOS app with 10+ core features
    • Implemented video calling and WebRTC communication systems
    • Built Human Fall Detection algorithm using YOLOv5 with 95% accuracy

Education

  • Jan 2024 - Dec 2025

    Evanston, Illinois

    Master of Science
    Northwestern University
    Artificial Intelligence
  • 2018.08 - 2022.09

    Bengaluru, India

    Bachelor of Technology
    PES University
    Electronics and Communication Engineering
    • Signal Processing
    • Embedded Systems
    • Digital Communications

Awards

Skills

Programming Languages
Python
SQL
C
Swift
Machine Learning & AI
PyTorch
Transformers
Sklearn
XGBoost
LangChain
LangGraph
LlamaIndex
PEFT
RLHF
Data & Infrastructure
Pandas
NumPy
ChromaDB
Elasticsearch
FastAPI
Flask
Docker
Research Areas
Large Language Models
Natural Language Processing
Reinforcement Learning
RAG Systems
Mechanistic Interpretability
Agentic AI

Languages

English
Native speaker
Hindi
Native speaker
Telugu
Native speaker

Interests

Artificial Intelligence
Large Language Models
Natural Language Processing
Reinforcement Learning
Mechanistic Interpretability
Agentic AI
Computer Vision
Research
Machine Learning
Deep Learning
Data Science
AI Ethics
Explainable AI

Projects

  • 2025.02 - 2025.02
    AdVocate - AI Marketing Platform
    Finalist for 'Best Use of Generative AI' at TartanHacks 2025, CMU. Engineered end-to-end AI marketing platform reducing campaign creation time by 90%.
    • Designed microservices architecture using Azure OpenAI, LangChain, and ChromaDB
    • Optimized API costs with two-tier caching, achieving 60% reduction in API calls
    • Built comprehensive marketing automation workflows
  • 2024.10 - Present
    Real-Time Options Trading Intelligence Platform
    Developing options prediction model combining statistical and neural architectures with real-time market data integration.
    • Building trading bot integrating real-time market data with sentiment analysis
    • Implementing statistical and neural network architectures for options prediction
  • 2020.09 - 2021.05
    E-yantra Robotics Competition
    Led 4-person team developing automated warehouse system using ROS and Gazebo, achieving competition score of 97.96/100.
    • Optimized simulation performance by 50% through multi-threading
    • Developed automated warehouse management system
    • Top performance achievement in national robotics competition