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:

AUTONOMYDon’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 and 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.FOCUSSmall 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 MEDIOCRITYGive direct feedback to everyone immediately rather than avoiding

unpopularity , expecting things to improve naturally, or

trading

short-term pain for long-term pain.Embrace an extreme learning rate rather than assuming limits to your ability/knowledge.Drive ownership to final outcome, despite barriers.Responsibilities

Design and implement systems for orchestration of ML execution—enabling training across our decentralised and heterogeneous infrastructure.Performance optimisation—continually profile and optimise our training algorithms.Implement novel research—develop mechanisms and algorithms to tackle new problems.Engineering support—collaborate on wider ML issues (e.g., reproducible training).Write and engage—contribute to technical reports and papers, and discuss with the community.Minimum requirements

Hands-on experience with distributed foundation model training, designing or working with large cluster training systems.Networking expertise—understanding and troubleshooting protocols like IP, TCP, UDP, HTTP; experience with NCCL, GLOO, MPI.Open source experience—contributing to large codebases as maintainer or trusted contributor.Willingness to learn Rust—since we are a Rust-based company, familiarity or readiness to learn is essential.Computer science background—knowledge of algorithms, data structures, and computational complexity.Self-motivated with excellent communication skills.Comfortable working in an autonomous, research environment with unpredictable timelines.Nice to haves

Experience in systems programming in Rust (knowledge of lifetimes, Pin, etc.).Research background in distributed systems or ML domains.Understanding of blockchain fundamentals.Compensation / Benefits:

Competitive salary, equity, and tokensFully remote work —we hire between West Coast (PT) and Central Europe (CET) time zones.Relocation assistance —available for those moving after hiring.Annual company retreats —4 fully paid trips worldwide.Equipment, paid sick leave, private health, vision, dental insurance —including dependents.

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