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Jignesh Patel
Junior Software Engineer specializing in backend and distributed systems
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About
Software engineer with a strong builder mindset who has worked across ML, backend, and frontend systems. Notably built an AI-driven predictive autoscaler for Kubernetes from scratch using Prometheus, TensorFlow, Flask, and Spring Boot, and also delivered customer-facing automation features in financial document processing by working directly with auditors to translate domain rules into product logic.
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Key Strengths
- Built full-stack predictive Kubernetes autoscaler end-to-end
- Strong ML engineering in time-series forecasting
- Hands-on ownership of data ingestion, training, and inference pipelines
- Pragmatic model selection and fallback design using LSTM and Prophet
- Customer-driven product development with direct auditor collaboration
- Solved messy real-world document and Excel parsing problems
- Adapted across Java and Python to overcome library limitations
- Search relevance tuning across BM25 and vector retrieval
- Performs well in ambiguous, zero-to-one environments
- Applied domain knowledge to simplify calculations and improve performance
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