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Tejaswini P
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
Austin, TXML Engineer3 years experienceMid-LevelFinancial ServicesEducationEnterprise Software
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About
Built and deployed an LLM-powered financial/regulatory document analysis platform at State Street, combining fine-tuned transformer models with a RAG pipeline over internal knowledge bases. Owned the productionization stack (FastAPI, Docker, SageMaker, Terraform, CI/CD) plus monitoring for drift/latency/hallucinations, delivering ~40% faster analyst review and improved reliability through chunking/embeddings and grounding.
Experience
ML EngineerState Street
Graduate Research Student – Machine LearningUniversity of Central Missouri
Associate Software EngineerInfor
Python DeveloperKoderbox Technologies
Education
University of Central Missourimaster, Computer Science (2025)
Key Strengths
- Deployed LLM/RAG system to production on AWS SageMaker with CI/CD and Terraform
- Improved analyst review time by ~40% via automated extraction/summarization/anomaly detection
- Solved long-document token limit issues using chunking + embeddings-based retrieval
- Reduced hallucinations by grounding outputs with RAG against internal knowledge bases
- Balanced latency and cost by fine-tuning smaller models and adding caching
- Built robust monitoring for latency, drift, and hallucination rates (CloudWatch, MLflow, Prometheus)
- Orchestrated end-to-end ML workflows with Airflow and event-driven AWS Step Functions/Lambda
- Effective collaboration with product and compliance stakeholders using plain-language alignment and iterative feedback
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