Research Associate

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.

The Role

• Craft high-signal technical writing and content that translates Gensyn’s cutting-edge ML and distributed systems research into clear, compelling narratives for a variety of target audiences

Responsibilities

• Work closely with researchers, engineers, and leadership to deeply grok research and engineering developments across Gensyn
• Write compelling long-form essays, technical explainers, and narrative pieces about ML, distributed compute, cryptographic proof systems, and related technologies
• Translate dense technical concepts into clear, engaging language that appeals to both technical and strategic audiences
• Shape Gensyn’s voice in the ML and infrastructure ecosystem through writing that is magnetic and rigorous
• Conduct interviews, read papers & code, and extract the “why it matters” behind our work
• Support go-to-market and community efforts with thought leadership that attracts talent, developers, and partners

Competencies

Must Have

• Exceptional writing skills, with a portfolio of published work on ML, systems, and/or decentralisation topics
• Experience collaborating with engineering and research teams to produce deeply technical content
• Proven ability to learn fast and explain hard things via writing, teaching, or product evangelism
• Deep interest in deep learning,the societal effects of AI , and decentralised systems
• Comfort navigating extreme ambiguity and independently determining and driving editorial strategy

Preferred

• Experience working in high-growth startup and/or scaleup environments

Nice to have

• Previous experience as a Machine Learning Researcher or Machine Learning Engineer
• Experience speaking at technical conferences and/or speaking on technical podcasts
• Familiarity with ZK proofs, blockchain infrastructure, and/or cryptographic protocol design
• A strong network or public presence in the ML or AI community

Compensation / Benefits

• 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]

Our 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.
• Build and design thinly.