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Gabrielle Burns
Senior AI/ML Engineer specializing in computer vision, NLP, and enterprise ML systems
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ML/AI engineer with hands-on ownership of production computer vision and GenAI systems, spanning real-time public safety video analytics and RAG-based knowledge assistants. Stands out for translating research-oriented approaches into scalable, monitored production systems with clear business impact, including 50% latency reductions, 25% faster response times, and 40% lower document search time.
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Key Strengths
- owned end-to-end ML system deployment for real-time public safety video analytics
- reduced inference and p99 latency by 50%
- improved public safety response times by 25%
- strong production ML infrastructure skills across Docker, AWS, Kubernetes, Prometheus, and Grafana
- shipped RAG-based document assistant with measurable product impact
- reduced document search time by 40%
- improved LLM safety and factuality with retrieval thresholds, re-ranking, prompt constraints, and fallback responses
- balanced latency, cost, and quality tradeoffs in production semantic search and RAG systems
- built reusable Python ML pipeline framework used across multiple teams
- improved reproducibility and reduced integration bugs through modular APIs, pytest, CI/CD, and MLflow
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