Isha Kookanapalli math

Software Engineer

Brooklyn, New York, United States0 mo experience
AI EnabledAI ML Practitioner

Key Highlights

  • Expert in building end-to-end AI systems.
  • Proven track record in improving model performance.
  • Strong data engineering and analytics background.
Stackforce AI infers this person is a skilled AI Engineer with expertise in LLM systems and data engineering.

Contact

LinkedIn

Skills

Core Skills

React.jsNext.jsArtificial Intelligence (ai)Large Language Models (llm)Machine LearningData Engineering

Other Skills

REST APIsTestingPython (Programming Language)Prompt Engineeringmodel evaluationNatural Language Processing (NLP)Neo4jExtract, Transform, Load (ETL)SQLC++ResearchObject-Oriented Programming (OOP)Data AnalyticsWeb Development

About

I’m an AI engineer focused on building practical, product-oriented systems using LLMs, automation, and data-driven workflows. I’ve worked across the full lifecycle of applied AI systems from designing prompt pipelines and evaluation frameworks to integrating models into real-world applications. At Handshake, I improved LLM-based code generation systems by increasing accuracy and reducing error rates through structured evaluation and workflow design. Beyond AI systems, I’ve built production-facing features using React/Next.js and integrated them with backend APIs, as well as developed computer vision pipelines for real-world applications. I’m comfortable working across the stack to take ideas from prototype to usable product. I also bring strong data engineering and analytics experience, including working with data pipelines, model evaluation, and debugging model performance allowing me to build systems that are not just intelligent, but reliable and measurable. I focus on building end-to-end AI systems that combine model performance, data pipelines, and product workflows. I’m currently seeking full-time AI Engineer (Applied/Product-focused) roles starting May 2026.

Experience

0 mo
Total Experience
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Average Tenure
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Current Experience

Tiny archives

Software Development Intern

Feb 2026 – May 2026 · 3 mos · New York City Metropolitan Area · Remote

  • Developed a React/Next.js feature to streamline internal workflows, improving efficiency by 30%
  • Built reusable, accessible UI components (ARIA-compliant), reducing user errors and improving usability
  • Integrated frontend with backend APIs and validated flows using Jest and Playwright, reducing UI defects by 25%
Next.jsREST APIsReact.jsTesting

Handshake

Artificial Intelligence Engineer

Jan 2026 – Apr 2026 · 3 mos · New York, United States · Remote

  • Engineered prompt pipelines for LLM-based systems focused on Python and software engineering workflows, improving code generation accuracy by 25%
  • Evaluated and refined model outputs using structured evaluation techniques, reducing error rates by 30%
  • Improved real-world usability of LLM systems through iterative evaluation and feedback-driven workflow design
Artificial Intelligence (AI)Python (Programming Language)Prompt EngineeringLarge Language Models (LLM)model evaluation

New york university

2 roles

Graduate Orientation Leader

Aug 2025 – Aug 2025 · 0 mo · New York, United States

Peer Mentor

Jun 2025 – Aug 2025 · 2 mos · New York, United States

Nyu vertically integrated projects (vip)

Computer Vision / Machine Learning Researcher

Aug 2025 – Dec 2025 · 4 mos · New York, NY · On-site

  • Built an end-to-end computer vision pipeline for orthomosaic generation from aerial imagery
  • Applied feature extraction, image matching, and homography estimation to improve alignment accuracy
  • Improved robustness of image stitching workflows for real-world remote sensing applications
Natural Language Processing (NLP)Machine Learning

Getintro

Software Engineer Intern

Jun 2025 – Aug 2025 · 2 mos · Boston, MA · On-site

  • Built Neo4j-based ETL pipelines to process and structure large-scale graph data for downstream ML and analytics use cases
  • Optimized API-driven data retrieval and query performance, reducing response times by 30% and enabling faster model-driven insights
  • Implemented logging, monitoring, and validation workflows to improve pipeline reliability and reduce failure rates by 15%
Data EngineeringNeo4jExtract, Transform, Load (ETL)SQL

Tequed labs

AI/ML intern

Aug 2023 – Sep 2023 · 1 mo · Bengaluru · On-site

  • Built and experimented with machine learning models for classification and prediction tasks using Python and standard ML libraries
  • Performed data preprocessing, feature engineering, and evaluation to improve model performance
  • Gained hands-on experience in end-to-end ML workflows, including training, validation, and debugging model outputs

Codeclause

AI Intern

Feb 2023 – Mar 2023 · 1 mo · Bengaluru · Hybrid

  • Developed small-scale AI/ML projects involving data preprocessing, model training, and performance evaluation
  • Applied supervised learning techniques to solve practical problems and improve prediction accuracy
  • Strengthened understanding of ML fundamentals and real-world model behavior through experimentation

Education

New York University

Master of Science - MS — Computer Engineering

Aug 2024 – May 2026

JSSATEB, Bengaluru

B.E. — Computer Science & Engineering

Jan 2024 – Present

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