Meisam Ghafarlangroudi-AI Product Engineering Lead | Hands-On Delivery, Clients & Platforms

Geeks Ltd is a UK-based technology company; WordUp is its AI-driven language-learning product focused on personalized vocabulary learning and intelligent educational experiences.

• Coordinate AI product delivery across Product, Engineering, Data, Operations, and leadership, translating user needs into scoped initiatives, sequencing work, surfacing blockers, facilitating hand-offs, and communicating progress.
• Own search, recommendation, retrieval, and content-enrichment features end to end, from requirements and architecture through Python/FastAPI implementation, testing, deployment, monitoring, and rapid iteration.
• Developed low-latency retrieval, ranking, and personalization services using AWS, OpenSearch, DynamoDB, embeddings, and reusable APIs, achieving <1s latency, 22% higher engagement, and 12% higher premium conversion.
• Use AI coding assistants for codebase analysis, scaffolding, refactoring, tests, debugging, and documentation while reviewing every output for correctness, architectural fit, security, maintainability, and user value.
• Represent technical work in planning and stakeholder discussions, gather requirements first-hand, challenge priorities constructively, explain delivery trade-offs, and help teammates make outcome-focused decisions.

Mellat Bank boasts a staggering customer base of over 50 million individuals in Iran. Renowned for its extensive range of offerings, the bank provides a comprehensive suite of services exceeding 100, including innovative options like Buy Now, Pay Later (BNPL) solutions.

• Developed a news trading algorithm using Fin-BERT and GPT3 and sentiment analysis to predict short-term price movements in Forex and Crypto markets, achieving a 20% improvement in trading signal accuracy
• Built an ensemble model combining XGBoost with a deep auto encoder to detect anomalies in credit card transactions in real time, reduced false positives by 25% and improved fraud recall by 15%
• Implemented a customer churn prediction model, reducing churn by 15% and enhancing customer retention strategies
• Built recommendation engines to suggest banking products to customers, enhancing cross-selling opportunities by 22%
• Developed a sentiment analysis model using BERT to analyze Instagram comments, achieving over 85% accuracy and providing actionable insights for customer engagement strategies
• Engineered a forecasting model using Deep AR to predict credit usage with an R-square value exceeding 80%, optimizing financial planning
• designed and implemented a credit risk scoring system that improved early identification of high-risk applicants and reduced default rates by 12%