Hi, I’m Yogesh

I am a senior AI/ML Engineer with 6+ years of hands-on experience building data-driven solutions at scale with a Master's in Computer Science from Cornell University. Specialized in NLP, Deep Learning, and MLOps with proven expertise in leading cross-functional teams and innovating end-to-end AI systems, from model research and development to production deployment and monitoring.
Yogesh Eshwar Patil
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Experience

Co-founder & ML Engineer, R2Decide Inc

Aug 2024 - Present (Ithaca, NY, USA)

  • Co-founded a startup to transform eCommerce with AI-driven discovery, personalized recommendations, and intent resolution
  • Onboarded a leading jewelry brand and an espresso machine manufacturer as development partners for search and chat agents
  • Improved search engagement rate by 54% by developing a hybrid vector search engine based on multimodal embeddings
  • Reduced zero click sessions by generating AI-driven personalized sales guidance and query refinement suggestions for searches
  • Enriched raw eCommerce product catalogs by designing a data enrichment pipeline on llava-onevision-qwen2-72b-ov-hf VLM
  • Developed an AI sales agent assisting customers make complex purchase decisions through dynamic and conversational sales plans

Senior Artificial Intelligence Engineer, Shell plc

Nov 2022 - July 2023 (Bengaluru, KA, India)

  • Developed and deployed deep learning models to forecast sulfur market prices, driving $4M in annual savings
  • Enhanced prediction accuracy by 15% in volatile markets through feature engineering with Bollinger Bands and MACD indicators
  • Secured negotiation advantages by optimizing neural network training for both short- and long-term sulfur price predictions
  • Maintained model accuracy above 85% by implementing MLOps pipelines for continuous monitoring and retraining
  • Provided real-time insights by creating API endpoints and integrating ML models into enterprise applications

Software Engineer - Data Analytics, Shell plc

Jan 2020 - Oct 2022 (Bengaluru, KA, India)

  • Increased operational efficiency and resource allocation by 60% for 10,000+ resources through an enterprise analytics platform
  • Engineered a resource allocation algorithm that smartly matched skills to project requirements, reducing costs by $250K annually
  • Optimized manual effort by 40% by designing load balancing algorithm that automatically mapped resource request assignments
  • Prevented 30% allocation gaps in upcoming year by forecasting project demand and resource availability with time-series models

Software Engineer - Data Migration, Shell plc

June 2017 - Dec 2019 (Bengaluru, KA, India)

  • Led the unstructured data migration in $50B British Gas acquisition, designing a tool and resolving dependencies with data owners
  • Built a unified data warehouse integrating 30M+ records from multiple enterprise sources for effective resourcing by 1,000+ managers

Education

Master of Engineering in Computer Science

Cornell University, Aug 2023 - May 2024 (Ithaca, NY, USA)

Relevant Coursework: Machine Learning, Natural Language Processing, Computer Vision, Robot Learning

Bachelor of Engineering in Computer Science

Ramaiah Institute of Technology, Aug 2013 - May 2017 (Bengaluru, KA, India)

Skills

  • Programming & Software Engineering: Python, C++, Java, R; APIs & Microservices; Git, OOP, Design Patterns
  • ML & Deep Learning: Supervised, Unsupervised, Reinforcement Learning, LSTM, Transformers
  • ML Frameworks: PyTorch, TensorFlow, scikit-learn, XGBoost; spaCy, BERTopic
  • Generative AI & RAG: Prompting, Fine-Tuning, Multimodal Embeddings, Vector Search, Re-rankers
  • Data Engineering & MLOps: SQL/NoSQL, ETL, Hadoop, Spark; Docker, CI/CD, FastAPI, AWS, Azure
  • Leadership & Management: Agile (Scrum), Stakeholder Engagement, Team Collaboration, Mentoring
  • Domain Expertise: eCommerce, Energy, NLP, Search, Recommender Systems

Projects

Clone Advisor, Cornell University

June 2024 - July 2024 (Ithaca, NY, USA)

  • Built a RAG-based support agent for a 5,000-member espresso community, offering expert coffee-making and troubleshooting advice
  • Implemented social-score based document ranking model, boosting rankings for reputed authors based on posts and comments

AutoML Performance in Noisy Environments, Cornell University

Aug 2023 - Dec 2023 (Ithaca, NY, USA)

  • Researched the impact of noise on AutoML frameworks (AutoKeras, TPOT) by simulating Gaussian and random noise environments
  • Demonstrated an 11.6% improvement in F1-score of AutoML frameworks by incorporating effective data cleaning strategies

Publications

Customer Churn Prediction for Retail Business

ICECDS, Aug 2017 - doi.org/10.1109/ICECDS.2017.8389557

  • Researched and modeled customer churn behavior leveraging transaction analysis and traditional machine learning algorithm

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