Machine Learning Scientist

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 team@bagel.net. We look forward to seeing how you think and what you create.