
ML Researcher (Internship and Full-time) at Tilde Research (San Francisco, CA)
Tilde Research· San Francisco, CA·
Role details
Work type
Onsite
Employment
Full-Time
Job description
Tilde Research is a moonshot AI lab advancing mechanistic interpretability, new architectures, and pretraining science. We build foundational understanding of models to advance the frontier of intelligence.
About the role: As a ML Researcher, you will develop innovative techniques to deeply understand how large AI models work—and use those insights to make them better. You'll work on training, analyzing, and evaluating cutting-edge models, collaborating closely with a team of researchers and engineers to advance interpretability as a tool for improving performance and control.
What you might work on:
- Designing, prototyping, and optimizing novel model architectures
- Investigating why models or specific components behave the way they do—and how to improve them
- Curating targeted datasets to elicit and instill specific behaviors or capabilities in models
- Collaborating on papers, blog posts, and open-source tools to share insights with the broader community
You're a good fit if you:
- Have experience in deep learning or related research areas
- Have deep technical expertise in some subfield(s) of modern ML, e.g. architecture, optimizers, RL, learning dynamics, etc.. This can include through:
- Strong publication record
- Thoughtful technical blog posts
- Have experience working with large-scale pre/post-training infrastructure for experimentation
- Communicate clearly and effectively, both verbally and in writing
- Can come up with and evaluate research ideas
- Are able to learn quickly
Why work at Tilde Research
- Cutting‑edge research – work on the hardest problems in AI interpretability and architecture design.
- Small lab culture (≈6 people) – high ownership, rapid iteration, direct impact on flagship projects.
- Moonshot mentality – not product‑driven, but driven by the pursuit of understanding; ideal for researchers who value fundamental science.
- Strong network effects – team members come from top institutions and labs; alumni go on to places like Nous Research, Forgepoint Capital, and Stanford.
- Career development – offers both internships and full‑time roles; the interview process includes a graph theory problem that showcases the lab’s intellectual rigor.
- Location: San Francisco (headquarters) – likely in‑person or hybrid given the small team size; specific remote policy is not publicly stated.