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Uday kumar swamy
Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI
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Built a production LLM-agent framework for a startup that performs daily financial/trading analysis by combining live market data with internal tools, including a centralized memory module to prevent context drift and reduce hallucinations. Also implemented an Airflow-orchestrated retail price forecasting pipeline deployed to AWS endpoints, scaling parallel workloads via Kubernetes Executor and validating systems with rigorous functional + LLM-specific metrics and cross-team collaboration.
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Key Strengths
- Built and deployed an LLM-powered financial analysis/trading strategy agent with risk/reward explanations
- Designed centralized agent memory to persist intermediate results and reduce context drift/hallucinations
- Optimized LLM cost/latency via caching, adaptive throttling, and compressed context using cheaper summarization models
- Established LLM-specific evaluation metrics (tokens/request, TPM/RPM, cache hit rate, latency) plus functional/integration testing
- Production workflow orchestration with Airflow for end-to-end ML pipelines (data → features → training → tuning → packaging → deployment)
- Improved Airflow parallelism by decomposing tasks and scaling with Kubernetes Executor
- Cross-functional collaboration with quant/data, backend/DevOps, product, and QA to validate strategies and productionize systems
- Able to translate non-technical business needs into ML requirements and deliver usable outputs (visuals + feedback loops)
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