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Machine Learning Scientist
We are a frontier research lab driving the future of decentralized open-source AI. Our core team includes specialists in cryptography, computational economics, and large-scale deep learning who have published at top-tier venues. We collaborate on next-generation models and often incorporate insights from new arXiv papers before they become mainstream.
Role Overview
We encourage curiosity-driven research and welcome bold, untested concepts. You will explore new theories and AI model architectures, conduct proofs-of-concept, and fuse ideas from ML, math, and cryptography. Our environment demands both creativity and rigor. We love novel insights backed by strong experimentation or formal justification.
Key Responsibilities
- Investigate or develop new AI methodologies that might reshape decentralized model training.
- Rapidly prototype research ideas using PyTorch, TensorFlow, or custom CUDA kernels.
- Collaborate with cryptographers and economists to integrate secure, incentive-aligned protocols into AI model pipelines.
- Share findings through internal research notes, external blog posts, and conference-level papers. Examples: blog.bagel.net
- Contribute to open-source projects, mentor junior team members, and maintain close ties with the broader research community
Who You Might Be
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 foundation in modern deep learning, including Transformers, Diffusion and large-scale optimization
- Exposure to at least one specialized domains like RL, Mixture-of-Experts, diffusion modeling, or distributed training.
- Solid grounding in mathematics and statistics for designing and interpreting novel experiments.
- Clear and concise communication style in both written and spoken form.
- Bonus: familiarity with cryptographic primitives, zero-knowledge proofs, or incentive design.
What We Offer
- A deeply technical atmosphere where complex ideas are pursued, challenged, and refined.
- Full remote flexibility within North American time zones.
- Competitive compensation with room to focus on open-ended research.
- Community-centric culture that prioritizes open-source impact and collaboration.
If you are compelled by research that fuses ML, cryptography, and distributed systems and are eager to work alongside a team with a track record of tackling novel challenges, we would love to hear from you.
Please email a link to a paper or project you have completed (rather than a traditional resume) to [email protected]. We look forward to seeing how you think and what you create.