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Neelesh Kumar

@neeleshkumar1

Senior AI/ML Engineer at Jeppesen ForeFlight building an agentic platform that extracts aerodrome operating minima with 98.7% accuracy.

India

Message

At Jeppesen ForeFlight, I’m leading the end-to-end design of an agentic AI platform that extracts Aerodrome Operating Minima from AIP charts across all countries, achieving 98.7% extraction accuracy. I’m also developing documentation and training cross-functional teams to support adoption of its AI-driven features.

At Boeing India Private Limited, I engineered and productionized FliteDeck Advisor, delivering 1.5–2% fuel savings per flight and $6M in annual revenue from Tier-1 airlines. I also developed an aviation chart extraction engine that saved 36K processing hours annually, and established Databricks infrastructure for distributed processing and production evaluation.

Experience

Work history, roles, and key accomplishments

Current

Senior AI/ML Engineer

Current

Jeppesen ForeFlight

Oct 2025 - Present (1 year 1 month)

Leading end-to-end design of an agentic AI data extraction platform automating Aerodrome Operating Minima calculations from AIP charts, achieving 98.7% extraction accuracy. Developing comprehensive developer documentation and training cross-functional teams to strengthen adoption of AI-driven features.

Agentic AI Generative AI Data Extraction Technical Documentation AI Adoption Training

Senior Data Scientist

Boeing India Private Limited

Nov 2021 - Oct 2025 (3 years 11 months)

Engineered and productionized FliteDeck Advisor for optimal Cost Index selection, delivering 1.5–2% fuel savings per flight and $6M annual revenue. Developed a hybrid CNN–Transformer aviation chart extraction engine, saving 36K processing hours annually, and deployed time-series-based altitude and wind optimization models to improve fleet fuel efficiency.

Machine Learning Recommendation Systems CNN Transformers Time Series Databricks PySpark Tableau Mentorship GenAI

Machine Learning Engineer

Honeywell Technology Solutions Lab

Mar 2019 - Nov 2021 (2 years 8 months)

Built Hadoop and PySpark pipelines processing ~4TB of flight data per aircraft for large-scale analytics and ML workloads. Delivered 20+ zero-defect production automation solutions, developed a Python-based compression utility reducing build cycle time by 99%, and designed a DNN-based recommendation system for aircraft-to-route assignments.

Hadoop PySpark Python Automation Tableau Deep Learning Recommendation Systems Flight Safety