Akshar Vandara

About

UE5 gameplay scripter (Blueprint-focused) from small startup teams who specializes in setting up core project architecture (game loop/data flow, controller, game instance, UI/menu) and building modular systems reused across multiple games. Rebuilt a save-system architecture from scratch to replace a problematic asset and improve scalability/maintainability, and has hands-on performance optimization experience (profiling, level streaming, Nanite-to-LOD tradeoffs). Also implemented a realistic cricket match simulation using Markov chains and transition matrices.

Experience

Education

Key Strengths

• Built scalable UE save system from scratch using built-in SaveGame support
• Re-architected and replaced a faulty third-party/store asset to improve reliability and team adoption
• Designs modular gameplay systems reused across multiple games (save/menu/FPS-TPS setup)
• Performance optimization using UE profiling; eliminated expensive per-tick casting
• Implemented level streaming to maintain stable frame rate in large continuous levels
• Made asset-performance tradeoffs (Nanite to traditional LODs) to hit performance targets
• Sets up foundational project systems (controller, core game loop/data flow, game instance, UI/menu)
• Algorithmic sports simulation using Markov chains/transition matrices for realistic match outcomes
• Built end-to-end cricket match simulation logic using Markov chains/transition matrices
• Balanced realism vs. player pacing by hiding full simulation under the hood and adding replay + speed controls (2x/4x/8x/16x)
• Rapid UE5 iteration cycle from idea to playtest (~6 weeks) with repeated playtest loops
• Incorporated external streamer feedback while using internal team for technical QA/bug replication
• Designed engagement/progression loop with card rarities/levels and anti-burnout timer/life system
• Implemented complex UE AI using Behavior Trees + EQS, including a final-boss 'Machine of War' that mirrors player abilities
• Refactored user-profile database schemas and reduced cloud function calls to lower real-time service costs and improve stability