Software Development, Machine Learning​/ ML Engineer, AI Engineer (Applied​/Software)

Machine intelligence will soon take over humanity’s role in knowledge-keeping and creation. What started in the mid-1990s as the gradual off-loading of knowledge and decision making to search engines will be rapidly replaced by vast neural networks - with all knowledge compressed into their artificial neurons. Unlike organic life, machine intelligence, built within silicon, needs protocols to coordinate and grow. And, like nature, these protocols should be open, permissionless, and neutral.

Starting with compute hardware, the Gensyn protocol networks together the core resources required for machine intelligence to flourish alongside human intelligence.

• You tell us!

• Further our mission to build the infrastructure to train ultra-high scale, open source, foundation models

Must Have

• Autonomy - able to drive things forward in a high entropy environment
• Deep appreciation of small-scale, high-powered teams

Preferred

• Web3 experience - previously worked on a low-level web3 protocol
• Machine learning experience - previously worked closely with ML technologies as a developer or power user

Nice to Have

• Cryptography engineering (with a focus on GPUs)
• Understanding and navigating AI & Crypto regulations
• Cryptoeconomics and game theoretic design
• 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 .