Founding ML Engineer in the Flower Frontier Model Team (all seniority levels welcome) [UK, Germany, Global]

Do you want to push the boundaries of what frontier AI models can be? Join as one of the founding members of the Flower Frontier Model Team, a new group at Flower Labs charged with building category-defining models that blend the bleeding-edge in existing practices together with Flower’s pioneering decentralized learning methods . This is a fundamentally different direction than the one vanilla frontier labs are taking, one that not only eases the path to GPU scaling but also unlocks new data silos currently unable to be leveraged for frontier model training. We will ship models with superhuman capabilities in domains spanning science, health, finance, drug discovery, and more. This is an opportunity to help invent and build the training paradigms that will define the next decade of AI, and to work on technologies that others will study, emulate, and build upon. About the Role (Preference given to candidates with post-training expertise. But any talented individual with a track record of exceptional drive and determination are encouraged to apply regardless of prior experience.) As a founding ML Engineer in this new team, you will play a critical role in building SOTA LLMs and foundation models within a small, high-impact team composed of contributors that have a mix of both research and engineering backgrounds. This role combines fast-paced development with disciplined software engineering: you will help build a reliable, maintainable and scalable software stack and use this to produce world-leading models that are open-sourced and integrated into new Flower Lab products. You will design, implement and optimize core components across the full spectrum of stages relevant to frontier model building: data curation, evals, pre-training, post-training — everything is in scope as the team seeks to release its first series of models. Experience in these areas is obviously welcome, but a general expectation of problem solving, learning on the job and working collaborativel