The Role
- Own and pursue novel research - building scalable, distributed models over uniquely decentralised and heterogeneous infrastructure
Responsibilities
- Publish novel research in deep learning focusing on massive scale modular/composable architectures, verifiability, and continual learning
- Research novel model architectures - design, build, test, and iterate over completely new ways of building neural networks
- Publish & collaborate - write research papers targeting top-tier AI conferences such as NeurIPS, ICML, ICLR and collaborate with experts from universities and research institutes
- Partner closely with research and production engineering teams to experiment and productionise the research
Must have
- Demonstrated background with novel research in machine learning via first author publications
- Comfortable working in an applied research environment with extremely high autonomy and unpredictable timelines
- Highly self-motivated with excellent verbal and written communication skills
Preferred
- Existing work in modular, highly distributed, or continual deep learning
Nice to have
- Experience with cryptography applied to machine learning
- Strong public presence
- Competitive salary + share of equity and token pool
- Fully 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]
- 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
- 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.