Remote Software Engineer - Distributed ML Training - Gensyn

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

REJECT MEDIOCRITY

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 & 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 tokens

Fully 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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