Research Intern

Responsibilities

• Contribute to cutting-edge research in scalable, distributed machine learning systems alongside experienced researchers and engineers.
• Explore new ways of building and verifying neural networks that operate across huge, decentralised, topologies of heterogenous devices.
• Design and prototype novel neural network architectures for decentralized compute environments.
• Contribute to joint publications and projects in collaboration with academic and industry researchers targeting top-tier AI venues such as NeurIPS, ICML, and ICLR.

Competencies

• Must Have:
• Currently enrolled in a PhD program (or, in exceptional cases, in a Master’s program) in Computer Science, Machine Learning, or a related field.
• Prior experience conducting original research, ideally with authorship or co-authorship on ML papers.
• A strong understanding of deep learning fundamentals and experience working with at least one major framework, e.g. PyTorch, JAX, or TensorFlow.
• A self-directed, curious, and autonomous individual who can thrive in an environment with high autonomy.
• Excellent written and verbal communication skills.
• Preferred:
• Research experience in distributed systems, continual learning, or modular neural architectures.
• A desire to contribute to open research and collaborate with the broader ML research community.
• Nice to Have:
• Experience at the intersection of cryptography and machine learning.

Benefits

• Competitive salary + share of equity and token pool.
• Full remote work - we currently hire between the West Coast (PT) and Central Europe (CET) time zones.
• Visa sponsorship - available for those who would like to relocate to the US after being hired.
• 3-4x all expenses paid company retreats around the world, per year.
• Whatever equipment you need.
• Paid sick leave and flexible vacation.
• Company-sponsored health, vision, and dental insurance - including spouse/dependents [🇺🇸 only].

Principles

• Autonomy & Independence:
• Don’t ask for permission - we have a constraint culture, not a permission culture.
• Claim ownership of any work stream and set its goals/deadlines, rather than waiting to be assigned work or relying on job specs.
• Push & pull context on your work rather than waiting for information from others and assuming people know what you’re doing.
• Communicate to be understood rather than pushing out information and expecting others to work to understand it.
• Stay a small team - misalignment and politics scale super-linearly with team size. Small protocol teams rival much larger traditional teams.
• Rejection of Mediocrity & High Performance:
• Give direct feedback to everyone immediately - rather than avoiding unpopularity, expecting things to improve naturally, or trading short-term pain for extreme long-term pain.
• Embrace an extreme learning rate - rather than assuming limits to your ability / knowledge.
• Don’t quit - push to the final outcome, despite any barriers.
• Be anti-fragile - balance short-term risk for long-term outcomes.
• Reject waste - guard the company’s time, rather than wasting it in meetings without clear purpose/focus, or bikeshedding.