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Prashanth Kedri
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and predictive maintenance
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About
ML engineer with General Motors experience deploying production AI systems, including a BERT-based sentiment classifier for over a million customer support call transcripts (reported ~91% precision) and sub-200ms latency via FastAPI/Docker optimization. Also built predictive maintenance models and automated retraining/monitoring workflows using Airflow and MLflow, collaborating closely with non-technical customer support stakeholders.
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Key Strengths
- Deployed BERT sentiment model to production for >1M customer support calls
- Achieved ~91% precision on sentiment classification
- Optimized production inference latency to <200ms (FastAPI + Docker + tuning/batching)
- Built automated retraining and monitoring pipelines using Airflow
- Improved Airflow reliability by decomposing long-running jobs and adding retries
- Metrics-driven ML development with experiment tracking (MLflow)
- Ability to translate AI solutions for non-technical stakeholders (customer support team)
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