Thomas Robinson
Partner Engineer, Monetization
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolThomas Robinson is a Partner Engineer focused on monetization at Meta with 11 years of experience building technical partnerships and product integrations across AI, collaboration platforms, and enterprise services. He helped launch and scale Workplace and Quest for Business integrations with major partners like Google, Zoom, and Microsoft, then transitioned to leading Meta’s Llama partner engineering efforts and responsible-AI initiatives such as LlamaGuard. A hands-on ML engineer in the open-source Llama Cookbook, he extended the project to support remote LLMs (OpenAI, Anyscale, Together) and contributed upgrade scripts and security demos that make Llama easier to adopt across providers. His background blends rigorous engineering from an Imperial College MEng in Aeronautics with applied simulation and systems roles at McLaren Applied and Rolls-Royce, giving him a rare combination of systems thinking and product-facing partner delivery. Based in London, he’s as comfortable in pre-sales and platform modernization as he is in coding integrations that bridge research models to production partners.
11 years of coding experience
14 years of employment as a software developer
MEng Aeronautical Engineering, MEng Aeronautical Engineering at Imperial College London
Github Skills (9)
llama10
openai10
python10
ai10
fine-tuning10
langchain9
llm9
machine-learning9
pytorch9
Programming languages (6)
Github contributions (5)
meta-llama/llama-cookbook
Jan 2024 - Dec 2024
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
ML EngineerContributions:6 reviews, 13 PRs, 3 pushes in 10 months
Contributions summary:Thomas primarily focused on enhancing the Llama Cookbook by integrating external LLM models. This includes creating a new `llm.py` class to interface with remotely hosted models like OpenAI, Anyscale, and Together, enabling the use of these models within the cookbook's inference workflows. Additionally, the user contributed to the code by adding examples and documentation and modifying prompt format utils for Llama Guard version upgrades. They also provided a code security demonstration. Furthermore, they added an example upgrade script to the Llama 3.1 repository to align the models.
aifinetuninglangchainllamallama2
tryrobbo/azure-docs
Feb 2018 - Mar 2023
Contributions:2 pushes in 5 years 1 month
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