Yuming Dai — Senior Machine Learning Engineer

Work Experience

1. Company: Mashgin
   Title: Senior Machine Learning Engineer
   Project: Autonomous Self-Checkout Kiosk Intelligence
   Duration: 11/2024 – Present
   Summary: Contributed to the transformation of Mashgin's self-checkout kiosks by creating an autonomous cognitive 'agent', which significantly reduced exceptional transactions and improved checkout throughput and sales.
   Responsibilities: Architecting AI system, engineering multi-modal agents, deploying continuous-learning pipelines, leading 'agent lifecycle' definition, delivering business outcomes, orchestrating integrations, mentoring the engineering team, steering research to production, and ensuring the agent architecture remained cutting edge.
   Technologies: 3D point-clouds, computer vision, policy modules, microservices architecture, edge-model deployments, reinforcement learning, CI/CD, telemetry, A/B testing
   

• Company: EliseAI
  Title: Machine Learning Engineer
  Project: Agentic Conversational AI System
  Duration: 10/2023 – 10/2024
  Summary: Led the development and deployment of EliseAI's high-throughput agentic conversational AI system for housing and healthcare clients, achieving 24/7 operations and increased conversion rates.
  Responsibilities: Architecting AI platforms, building intent-recognition engines, fine-tuning LLM pipelines, integrating with CRM/PMS systems, delivering A/B testing frameworks, launching product features, building predictive modeling pipelines, collaborating across teams, mentoring engineers, and driving a vertical-first AI strategy.
  Technologies: Python, microservices, natural language processing, LLM, Snowflake, Amazon S3, ensemble and deep-learning models, voice/NLP libraries, CI/CD
  
• Company: Grammarly
  Title: AI Researcher
  Project : Advanced Writing Assistance EngineComp
  Duration: 10/2020 – 10/2023
  Summary: Spearheaded the enhancement of Grammarly's writing-assistance engine, advancing the capabilities in grammar, style, tone, and correction with impactful features such as 'compose' and 'rewrite'.
  Responsibilities: Developing deep-learning models, crafting a hybrid architecture with classic NLP and transformer-based models, launching generative-AI features, constructing datasets for various writing tasks, and collaborating with teams to create a responsible AI framework.
  Technologies: Deep learning, NLP, transformer-based encoders/decoders, generative AI, dataset construction, real-time inference stacks, bias-monitoring
  
• Company: Lily AI
  Title: Machine Learning Engineer | Full Stack
  Project: Product-Content Enrichment Platform
  Duration: 09/2017 – 09/2020
  Summary: Led the full-stack development of Lily AI's product-content enrichment platform, which provided deep-learning powered attribute extraction, significantly enhancing clients' e-commerce personalization and conversion.
  Responsibilities: Creating the architecture for ML pipelines and full-stack services, deploying product-attribute extraction engines, designing backend services and front-end dashboards, integrating with retailer systems, and instituting MLOps practices.
  Technologies: Python, Flask, Docker, Kubernetes, React, Redux, ResNet, Inception, transformer-based text models, microservices, backend and frontend development
  

Education

• Master of Artificial Intelligence
  New York University
  09/2015 – 08/2017
  
• Bachelor of Computer Science
  New York University
  09/2011 – 08/2015