Location: New York City

Remote: Yes, but prefer in-office

Willing to relocate: Yes, to the Bay Area

Technologies: machine learning, transformers, LLMs, finetuning, flow matching, JAX, PyTorch, Python

Resume: https://www.echonolan.net/resume/cv.pdf

Email: echo@echonolan.net

I'm an ML engineer/ML research engineer looking for roles where there are gradients to descend, models to build, and/or datasets to gather. In general I want to advance the frontier of what's possible. My credentials are more towards research engineering than applied work, but I'm open to both. My last job was as a contract research engineer doing AI safety work at Redwood Research. I spent about half my time on our synthetic datasets of safe & unsafe LLM behavior, and the other half on fancy finetuning. I finetuned an LLM to exhibit unsafe behavior while fooling logistic probes trained to detect it, but only in deployment. Weird multi-part composite loss. My other big project is independent research in text-to-image models that are trained solely on unlabeled image data, exploiting CLIP embeddings for the link between text and images. Currently fighting with spherical flow matching models and racing the ICLR paper deadline.

If you need help getting ML systems up and running, getting them fast and correct, or if any of that stuff sounds interesting to you, get in touch.