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AI Dev Day - Building AI workloads from Experiment to Production

Event artwork for AI Dev Day - Building AI workloads from Experiment to Production

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About this event

What to expect

Scale your AI workloads from experimental prototypes to production-ready systems at this comprehensive technical event for ML engineers, AI developers, and data scientists. Hosted by the NYC AI/LLM/ML Developers Group, this full-day programme combines expert-led keynotes, real-world case studies, and intensive hands-on workshops designed to accelerate your path to production AI.

What You'll Experience

This event bridges the gap between AI experimentation and production deployment through three distinct components. The morning session features community-led talks sharing proven architectures, scaling patterns, and real-world lessons from teams who've successfully deployed AI systems at scale. You'll gain direct access to industry experts and power builders who've navigated the challenges of production AI firsthand.

The afternoon offers two parallel hands-on workshop tracks, allowing you to dive deep into specific technical areas. Choose between fine-tuning Vision-Language-Action (VLA) models for physical AI applications or mastering distributed training with Ray and PyTorch. Both workshops provide instructor-led guidance and practical experience with cutting-edge frameworks.

Workshop Tracks

VLA Track: Fine-tune VLA models for physical AI explores the intersection of computer vision, language models, and robotics. You'll work through large-scale VLA fine-tuning, implement distributed training with Ray, and experiment with robotics simulation environments. This track is ideal for those building embodied AI systems or working at the intersection of ML and robotics.

Ray Track: Run Distributed training with Ray and PyTorch focuses on scaling Python workloads for production AI. You'll learn to scale Python applications using Ray, build robust multimodal data pipelines, and implement distributed training architectures that can handle massive datasets and model sizes.

Who Should Attend

This event is designed for ML engineers, AI developers, data scientists, and technical leaders working to move AI systems from proof-of-concept to production. Whether you're struggling with scaling issues, looking to optimize your training pipelines, or seeking proven patterns for production deployment, you'll find practical solutions and peer insights from experienced practitioners.

The technical talks cover real-world architectures and scaling challenges, while the hands-on workshops provide imme

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