- π€ Build Production-Grade AI Systems β Develop end-to-end machine learning pipelines from research to deployment
- β‘ Performance Optimization β Reduce inference costs by 30% and latency by 50% through CUDA kernel optimization and intelligent caching
- π― Scalable ML Pipelines β Design and deploy distributed training systems, model quantization, and production-ready frameworks
- π Data Engineering β Build robust ETL pipelines processing millions of data samples with quality validation
- π Technical Leadership β Lead AI research initiatives, system architecture, and product strategy development
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