We are Bagel - a frontier research collective engineering the backbone of a decentralized, open-source AI economy.
Role Overview
We encourage curiosity-driven research and welcome bold, untested concepts. You will test hypotheses, invent architectures, and fuse ML with distributed systems. We love novel, provocatives ideas backed by strong experimentation or formal justification.
Key Responsibilities
- Prototype AI methodologies that can redefine distributed machine learning.
- Ship experiments in PyTorch, TensorFlow, or custom CUDA kernels at rapid cadence.
- Partner with cryptographers and economists to embed secure, incentive-aligned protocols into model pipelines.
- Publish papers at top-tier ML venues, organize workshops, and keep our roadmap aligned with the latest academic advances.
- Share insights through internal notes, external blog posts, and conference-grade write-ups (e.g., blog.bagel.net).
- Contribute to open-source code, mentor junior researchers, and stay active in the ML community.
Who You Might Be
You are extremely curious. You actively consume the latest ML research - scanning arXiv, attending conferences, dissecting new open-source releases, and integrating breakthroughs into your own experimentation. You thrive on first-principles reasoning, see potential in unexplored ideas, and view learning as a perpetual process.
Desired Skills (Flexible)
- Strong command of modern deep learning - Transformers, diffusion models, large-scale optimization.
- Depth in at least one area such as Reinforcement Learning, Mixture-of-Experts, LoRA/LoKR variants, expert routing & shard-aware scheduling, gradient compression, on-device federated RL or general distributed training.
- Solid mathematics and statistics foundation for designing and interpreting experiments.
- Clear, concise communication.
- Bonus: familiarity with cryptographic primitives like zero-knowledge proofs.
What We Offer
- A deeply technical culture where bold, frontier ideas are debated, stress-tested, and built.
- Full remote flexibility within North American time zones.
- Competitive compensation and time to pursue open-ended research.
- Ownership of work that can set the direction for decentralized AI.
- Paid travel opportunities to the top ML conferences around the world.