Machine Learning Scientist

Bagel Labs; Canada; Remote; CAD 150,000 - 240,000; Full time

Job summary

Bagel Labs is seeking a Machine Learning Researcher to explore innovative AI methodologies in a collaborative environment. The ideal candidate will have a strong foundation in deep learning and mathematics, and will engage in cutting-edge research that fuses ML, cryptography, and decentralized systems. This role offers full remote flexibility within North American time zones and competitive compensation focused on open-ended research.

Benefits

Full remote flexibility within North American time zones

Competitive compensation

Community-centric culture

Qualifications

• Strong foundation in modern deep learning, including Transformers and large-scale optimization.
• Solid grounding in mathematics and statistics for designing and interpreting experiments.
• Clear and concise communication style in both written and spoken form.

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 protocols into AI model pipelines.

Skills

Deep Learning

Mathematics

Statistics

Communication

Job description

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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 [e-mail]. We look forward to seeing how you think and what you create.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

• Industries

  Technology, Information and Internet

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