ineedasername

Location: Remote/Hybrid NYC area
Resume/CV/Experience: working demonstrations available below, anything else available on request.
Email: [email protected]
Seeking: applied AI, model behavior, evaluation, interpretability, inspectability, research engineering, synthetic data generation, or adjacent roles
I have spent more than 15 years building my own tools when the available ones were insufficient, and being someone sent when there was a problem, either to figure out what was going on or solve it, or both.
This has been as a generalist across analytics and data science for the operational arm of a large public university w/ steadily expanding domain responsibility, informing senior leadership, at times authoring strategy and policy. (I'm not as faculty, although I developed and taught a course for several years, Language of Propaganda, as an adjunct lecturer: adversarial uses of language examined through informal logic, cognitive blind spots, and case studies.) Separate from this, when a self-funding hobby found unexpected product-market fit I grew it to side-business and shipped 10,000+ items.
My academic background is in applied linguistics, NLP, cognitive science, and analytic philosophy. I might have followed a research or academic path, but by the time I completed my master's degree, I had concluded that the paths then available would not give me much room to pursue the questions I actually cared about.
Those interests are language, mind, cognition, and computation, all now converged in modern AI, I have devoted a lot of time bringing in ideas from traditional linguistics and some other areas and turning them into practical tools.
Recent work, including live demos:
- Cartogemma: A REPL-like environment for LLM inference. Explore generation as a branching process, preview output, inject tokens, rewind, ablate or restore heads, trace a chosen token through the layers. Per-head projections, residual contributions, the ordinary logit lens, and full-layer output side by side. The CMD/REPL bar functions once loaded. https://huggingface.co/spaces/anotheruserishere/Cartogemma
- Tokescope: watch a model in real time during inference, flag tokens to monitor & intervene. Catch something surfacing, before output. Once flagged it either logs it, stops the response with a hard gate, or suppresses using a gram-schmidt projection that takes the direction out of the vector. https://huggingface.co/spaces/anotheruserishere/Tokescope
- Bertographer is similar, runs on encoder models, classification task, ie NLI models, Also with ad-hoc steering https://huggingface.co/spaces/anotheruserishere/Bertographer
- An instrumentation and intervention library for examining model internals during inference & using them to decompose behavior and outputs. It's what provides core tooling for the HF spaces listed. It analyzes derived structure, across layers and heads. These traces then use linear-algebraic, statistical, and overlap methods such as SVD, PCA, correlation analysis, and Jaccard similarity, results of which can then be used to steer a model through targeted activation-space interventions.
- Another library builds off of this one in the direction of mechanistic interpretability, for finding SAE-like features without the hassle of training an SAE, providing a range of static and interactive visualizations, scanning & storing model states at some or all steps of inference, among other things.
If any of this maps onto a problem your organization has or a role for which you have not found an easy title I would be glad to talk: [email protected]