Machine learning models are revolutionizing our world—autonomous driving, detecting diseases, enhancing senses, and personalizing our experiences. In the coming years, AI will transform how we live, think, and grow, merging organic and machine intelligence.
Envision limitless content creation, personalized tutoring, and memory enhancements tailored to you. This future demands vast, globally accessible, and uncensorable computational power. Our goal is to turn machine learning compute into a ubiquitous resource—accelerating AI progress and ensuring this transformative technology is accessible to all through a free market.
Key Responsibilities:
Train highly distributed models on unique, decentralized infrastructure.
Research and design novel model architectures, testing new neural network builds.
Publish and collaborate on research papers for top-tier AI conferences.
Support the engineering team with broader ML issues.
Follow best practices in open-source development.
Write and engage in technical reports and community discussions.
Essential Requirements:
Strong research background with publications at major machine learning conferences.
Deep understanding of machine learning and distributed systems.
Hands-on experience with distributed model training.
Highly self-motivated with excellent communication skills.
Comfortable in an applied research environment with high autonomy and unpredictable timelines.
Preferred Qualifications:
Experience with communication backends (e.g., NCCL, GLOO, MPI).
Experience in training Large Language Models (LLMs)