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Vivek Reddy
Mid-level Data Scientist/Data Engineer specializing in ML pipelines, insurance and healthcare analytics
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About
Built a production assistive-vision iPhone app to help visually impaired users find grocery items, training a custom YOLO detector on 2,000+ self-collected/annotated images and deploying via CoreML with a cloud multimodal LLM for navigation instructions. Brings hands-on AWS serverless + ECS container deployment (CDK/GitHub Actions) and a disciplined approach to AI workflow reliability (state-machine design, offline evals, stress tests, logging/metrics), plus experience communicating model insights to non-technical stakeholders (MOTER Technologies).
Experience
Education
Key Strengths
- Built and deployed an assistive vision iOS app for visually impaired grocery navigation (YOLO + CoreML + cloud multimodal LLM)
- End-to-end ML pipeline ownership: data collection/annotation, training, deployment, and iteration
- Practical approach to dataset imbalance (targeted data collection + heavier augmentation for underrepresented classes)
- Strong AWS serverless and container orchestration experience (S3, API Gateway, Lambda, ECS, ECR, CDK, GitHub Actions)
- Systematic AI workflow design and evaluation (state machines, unit tests, offline prompt eval sets, stress testing, logging/metrics)
- Model/retrieval selection grounded in latency/cost/accuracy tradeoffs (e.g., YOLO vs transformer; FAISS vs Pinecone/OpenSearch)
- Effective debugging in CI/CD and cloud workflows (resolved 404s due to naming/config mismatches across ECR/Lambda/GitHub Actions)
- Able to translate ML insights to non-technical stakeholders using business-relevant explanations (feature importance example)
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