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

Role overview

Qualifications

  • Experience building or contributing to state-of-the-art LLMs and foundation models with a hands-on track record.
  • Familiarity with transformers, their variants, and optimization theory, including large-scale training stability.
  • Experience with SFT, preference modeling, RL and evals, and the ability to design and run systematic experiments.
  • Strong problem-solving, scientific rigor, and demonstrated potential for technical leadership in a fast-paced startup.

Responsibilities

  • Hands-on development of SOTA LLMs and foundation models, turning ideas into working systems; contribute to open-source and Flower Lab product integrations.
  • Design, prototype, and scale training paradigms, and run experiments across data curation, evals, pre-training, and post-training.
  • Provide technical leadership within a small, high-impact team; collaborate across disciplines and influence product direction.
  • Contribute to releasing the first series of models, including open-source pipelines and deployment into Flower Lab products.

About the company

Flower Labs logo

Flower Labs

Artificial Intelligence & Machine Learning Services

Flower is the leading open-source framework for training better AI on distributed data using federated learning and other privacy-enhancing technologies. Industry leaders use Flower to easily collaborate on model training and are starting to transform high-value verticals like telecommunications (Nokia), healthcare (Korean AI Center for Drug Discovery), finance ([stealth]), automotive (Porsche), and personal computing (Brave). All AI today is based on public data, imagine where AI could be if it used all of the worlds’ distributed private data.

Company details

IndustryArtificial Intelligence & Machine Learning Services
Company size11 - 50

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Job description

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 Research 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 will provide the opportunity to shape every part of the scientific foundation of our frontier models. You’ll be deeply hands-on, turning your best ideas into working systems and collaborating with the team to scale the approaches that prove most effective. The methods you develop will be used to produce world-leading models that are open-sourced and integrated into new Flower Lab products.

We expect you to bring to the team creativity, balanced against systematic experiments, and a keen awareness of the latest result from other AI labs. This will feed into how you design and implement techniques and run experiments across the spectrum of stages relevant to frontier model building: data curation, evals, pre-training, post-training. Everything is in scope for you 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 collaboratively to efficiently combine the talents of the team is an explicit requirement for success. Familiarity in some mix of areas including the following will be necessary: transformers and their variants; optimization approaches — incl. theory and trade-offs; large-scale training stability; and finally, SFT, preference modeling, RL and evals.

This is a foundational role for an ambitious technical effort. We are looking for a special talent that brings to the team a strong principled scientific approach coupled with a talent for prototyping and all kinds of implementations. We seek out those able assume technical leadership as the ambitions of our models scale in complexity and capability. More broadly, you can expect a collaborative, fast-paced and demanding start-up environment containing a team of experts in their respective fields, in which everyone still learns something new every day. You will have the opportunity to contribute ideas, be heard and influence the direction of the company across the board.

About the Company

Flower Labs is the world-class AI startup best known for being behind the most popular open-source framework in the world for training AI on distributed data and compute resources using decentralized and federated methods. Trusted by industry leaders such as Mozilla, JP Morgan, Owkin, Banking Circle and Temenos use Flower to easily improve their AI models on sensitive data that is distributed across organizational silos or user devices. In a world where most AI relies on centralized public datasets — just a fraction of the data available — we believe unlocking access to (orders of magnitude more) sensitive data will drive the next breakthroughs in artificial intelligence.

Flower Labs is a Y Combinator (YCW23) graduate and backed by top-tier investors and renowned angels, including Felicis, First Spark Ventures, Mozilla Ventures, Hugging Face CEO Clem Delangue, GitHub Co-Founder Scott Chacon, Factorial Capital, Betaworks, and Pioneer Fund. Together, we are redefining how AI is built, deployed, and scaled.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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