After 11 consecutive years pushing the frontier from inside the big AI labs, I am spending some time working as an independent researcher in New York City.

Mar. 2025 – Jul. 2026

I was part of the founding team at Thinking Machines Lab. I worked on high-compute RL science, as well as long-term research that is difficult to categorize.

Sep. 2022 – Feb. 2025

At OpenAI, I landed contributions to most parts of the frontier deep learning stack:

• [2024-2025] on fundamental architecture research, designing a novel architecture component for inference efficiency.
• [2024] on pre-training, co-leading the GPT-4o bigrun.
• [2024] on mid-training, as overall tech lead of GPT-4o mini. I pitched this run, specced it for inference, executed its bigrun(s), and helped de-risk bleeding edge synthetic data recipes.
• [2023] on product x research co-design, conceiving of, training, and beta-releasing a high-compute agentic search system, an early predecessor of multi-agent “deep research” systems that are now common.
• [2022-2023] on post-training as part of the small research team that created ChatGPT, where I worked on RL science, co-designed key aspects of the tool-use ML, and helped tame the training effort into a repeatable “mainline” model training machine. My name is on some of the first GPT-4 post-trained checkpoints that served prod ChatGPT traffic.

I spun up, recruited, and briefly managed the London unit of OpenAI’s Training team.

Sep. 2015 – May 2022

DeepMind is where I came of age as a researcher. I was the padawan of Alex Graves, who is one of the field’s true greats. I worked on some of the earliest language model scaleups. Before the industrialization of deep learning, I contributed to the development of deep autoregressive architectures and generative modeling more broadly. See my Google Scholar page for published work. Some of this was undertaken as part of DeepMind’s joint PhD program with University College London (UCL).