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LLMOps is emerging as a critical enabler for organizations deploying large language models at scale – bringing data scientists, engineers, and end-users into tighter, more effective collaboration.
Join us for a deep dive into the operational backbone of successful LLM deployments. From model design to monitoring in production, you’ll learn how to unlock the full potential of LLMs with streamlined processes, smarter tooling, and cross-functional alignment.
In this session, you’ll explore:
🧠 What LLMOps is – and why it’s essential for scalable AI success
🔄 The full LLMOps lifecycle: from experimentation to deployment and iteration
🤝 How to accelerate collaboration between data teams, engineers, and business users
🧰 Practical frameworks and tools for building robust LLM pipelines
📊 Real-world case studies showcasing high-impact LLM applications
⚠️ Common challenges in LLMOps – and how to overcome them
Whether you’re an AI practitioner, developer, or team leader, this session will equip you with the insights and strategies to operationalize LLMs with confidence.
Meet the speaker:
Samin Alnajafi, AI Solutions Engineer, Weights & Biases
Samin Alnajafi is an accomplished Pre-Sales AI Solutions Engineer at Weights & Biases, specializing in AI-powered solutions for enterprise clients across EMEA. With experience at tech leaders such as Snowflake and DataRobot, he excels in guiding organizations through the technical intricacies of machine learning and data-driven innovation. His expertise spans large language model operations, sales engineering, and AI solutions, making him a valued advisor in deploying transformative technologies for a range of industries.
LLMOps is emerging as a critical enabler for organizations deploying large language models at scale.
