Offer summary

Qualifications:

Proven experience leading engineering teams in startups from inception to product launch., Strong leadership and communication skills, especially under pressure., Hands-on engineering experience in Machine Learning, Compilers, or Distributed Systems., Ability to attract and retain top engineering talent..

Key responsabilities:

Hire and manage high-performance engineering teams to deliver complex projects.

Mentor and incentivize team members to achieve high performance against tight deadlines.

Collaborate with the CTO and Technical Leads to scope and report on engineering deliverables.

Drive a culture of ownership and accountability within the team.

Job description

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

Hire, coordinate and drive 1-2 high-performance engineering teams

Responsibilities

Drive a culture of high performance - mentor, incentivize, and manage engineers to deliver highly complex and uncertain deliverables against tight deadlines
Lead and unblock members of your team whilst working closely with the CTO and Technical Leads to scope and report on engineering deliverables and timelines
Hire and retain world class talent

Competencies

Must have

A track record of leading teams in scale/start-ups that went from ‘0 to 1’ and released their first products (as opposed to only maintaining existing products)
Exceptional leadership, communication, and drive - particularly when under pressure
Experience attracting and closing world-class engineers
Hands on engineering experience in (at least) 1 of the following 3 domains:
- Machine Learning
- Compilers
- Distributed Systems

Preferred

Experience working cross-functionally with research teams

Nice to have

Rust programming knowledge
Meaningful exposure to cryptocurrencies
Founding experience
Open source contributions

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.

Required profile