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Pooja Dokuri
Mid-level AI/ML Engineer specializing in GenAI, RAG pipelines, and cloud MLOps
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About
Built and deployed a production LLM + vector search clinical decision support system at UnitedHealth Group, retrieving medical evidence and patient context in real time for prior authorization and risk scoring. Strong in end-to-end RAG architecture (Hugging Face embeddings, Pinecone/FAISS, SageMaker, Redis) plus orchestration (Airflow/Kubeflow) and rigorous evaluation/monitoring, with demonstrated ability to align solutions with clinical operations stakeholders.
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Key Strengths
- Built and deployed production LLM + vector search pipeline for clinical decision support
- Designed high-throughput real-time feature/data pipelines (Kafka + Spark)
- Handled noisy/inconsistent EHR data via normalization, deduping, and clinical entity mapping
- Implemented hybrid retrieval (BM25 + embeddings) to improve relevance with incomplete text
- Production optimization for low-latency retrieval at million-scale (caching with Redis)
- Hands-on orchestration across Airflow, Kubeflow Pipelines, and SageMaker Pipelines
- Reliability-focused evaluation approach (offline tests, A/B testing, monitoring/drift tracking)
- Effective collaboration with non-technical clinical stakeholders; translated needs into ML requirements
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