The world will be unrecognisable in 5 years.
Machine learning models are driving our cars, testing our eyesight, detecting our cancer, giving sight to the blind, giving speech to the mute, and dictating what we consume, enjoy, and think. These AI systems are already an integral part of our lives and will shape our future as a species.
Soon, we'll conjure unlimited content: from never-ending TV series (where we’re the main character) to personalised tutors that are infinitely patient and leave no student behind. We’ll augment our memories with foundation models—individually tailored to us through RLHF and connected directly to our thoughts via Brain-Machine Interfaces—blurring the lines between organic and machine intelligence and ushering in the next generation of human development.
This future demands immense, globally accessible, uncensorable, computational power. Gensyn is the machine learning compute protocol that translates machine learning compute into an always-on commodity resource—outside of centralised control and as ubiquitous as electricity—accelerating AI progress and ensuring that this revolutionary technology is accessible to all of humanity through a free market.
Our Principles:
AUTONOMY
- 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.
- No middle managers - we don’t (and will likely never) have middle managers.
FOCUS
- Small team - misalignment and politics scale super-linearly with team size. Small protocol teams rival much larger traditional teams.
- Thin protocol - build and design thinly.
- Reject waste - guard the company’s time, rather than wasting it in meetings without clear purpose/focus, or bikeshedding.
REJECT MEDIOCRITY
- 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.
- No quit - push to the final outcome, despite any barriers.
Responsibilities:
- Train highly distributed models over uniquely decentralised and heterogeneous infrastructure.
- Partner with both researchers and production engineers to design and run novel experiments, taking research from theory all the way to production.
- Own and maintain the experimental frameworks and test benches for ML research.
- Engineering support - work with the engineering team on wider issues concerning ML (e.g. reproducible training).
- Follow best practices - build in the open with a keen focus on designing, testing, and documenting your code.
- Publish & collaborate - write research papers targeting top-tier AI conferences such as NeurIPS, ICML, ICLR, AAAI, and IJCAI and collaborate with experts from universities and research institutes
Minimum requirements:
- Strong background in applied machine learning.
- Hands-on experience with distributed model training.
- Experience building highly performant, distributed systems.
- Comfortable working in an applied research environment - with extremely high autonomy and unpredictable timelines.
- Highly self-motivated with excellent verbal and written communication skills.
Nice to haves:
- Experience training highly distributed models.
Compensation / Benefits:
- Competitive salary + share of equity and token pool
- Fully remote work - we hire between the West Coast (PT) and Central Europe (CET) time zones
- Relocation Assistance - available for those that would like to relocate after being hired (anywhere from PST through CET time zones)
- 4x all expenses paid company retreats around the world, per year
- Whatever equipment you need
- Paid sick leave
- Private health, vision, and dental insurance- including spouse/dependents [🇺🇸 only]
