Eissa Jamil is a Partner Engineer AI at Meta with 11 years of software engineering experience spanning aerospace, interactive entertainment, AR/VR, and educational technology. He blends hands-on development (C++, C#, Python, Unity/Unreal) with partner-facing technical leadership, having managed teams and shipped interactive exhibits, theme-park attractions, and enterprise tooling. A contributor to the popular meta-llama/llama-cookbook, he has practical ML/LLM experience integrating Llama 2 with cloud providers like Amazon Bedrock and demonstrating prompt engineering patterns. Eissa’s background includes leading software efforts for the F-35 program and launching VR/IoT experiences for major brands, showing a rare mix of safety-critical systems and creative consumer-facing products. Based in Menifee, CA, he pairs technical depth with teaching experience and a curiosity about long-term technological trends that keeps him at the frontier of innovation.
11 years of coding experience
13 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Georgia Institute of Technology
Bachelor of Science Computer Science, Bachelor of Science Computer Science at San Diego State University
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Role in this project:
ML Engineer
Contributions:6 reviews, 3 PRs, 10 pushes in 5 months
Contributions summary:Eissa primarily contributed to the development and refinement of example notebooks related to prompt engineering with Llama 2 models, specifically integrating them with Amazon Bedrock. Their work involved setting up authentication, client configurations, and demonstrating the use of LangChain within the Bedrock environment. Key contributions include updating code examples, refining documentation, and updating model lists to encompass a broader range of models like Code Llama and Llama Guard. They also integrated the example of using ReAct with Llama 2 using Amazon Bedrock, and provided a detailed explanation of how to use the [INST] tag and the Llama 2 whitepaper.
Contributions:3 pushes, 1 branch in 1 year 9 months
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Eissa Jamil - Partner Engineer AI at Edge Technovations LLC