Location: New York, NY Remote: Preference for in-office/hybrid, open to remote Willing to relocate: no Technologies: machine learning, LLMs, flow matching, J

Location: New York, NY Remote: Preference for in-office/hybrid, open to remote Willing to relocate: no Technologies: machine learning, LLMs, flow matching, JAX, PyTorch, Python Resume: https://www.echonolan.net/resume/cv.pdf 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. If nothing goes horribly wrong I'll be submitting a paper for ICLR in about 7 weeks. 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.