Flower Labs
11 - 50 employees
Founded 2023
🤖 Artificial Intelligence
📚 Education
Artificial Intelligence • Software • Education
Flower Labs is a company that develops a friendly federated AI framework called Flower, which enables users to implement federated learning across various machine learning frameworks and programming languages. Flower aims to simplify the process of federated learning, allowing efficient distribution and execution of workloads across a multitude of clients. The platform is designed for scalability and usability, supporting diverse devices and cloud systems for research and production purposes.
Founding Research Engineer – Flower Frontier Model Team
Job not on LinkedIn
🕒 December 17, 2025
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Flower Labs
11 - 50 employees
Founded 2023
🤖 Artificial Intelligence
📚 Education
Artificial Intelligence • Software • Education
Flower Labs is a company that develops a friendly federated AI framework called Flower, which enables users to implement federated learning across various machine learning frameworks and programming languages. Flower aims to simplify the process of federated learning, allowing efficient distribution and execution of workloads across a multitude of clients. The platform is designed for scalability and usability, supporting diverse devices and cloud systems for research and production purposes.
📋 Description
• Push the boundaries of what frontier AI models can be • Build AI that blends cutting-edge techniques with Flower’s pioneering decentralized methods • Play a critical role in building SOTA LLMs and foundation models within a small, high-impact team • Shape every part of the scientific foundation of frontier models • Be deeply hands-on, turning best ideas into working systems • Collaborate with the team to scale effective approaches • Produce world-leading models that are open-sourced and integrated into new Flower Lab products • Develop methods for data curation, evals, pre-training, and post-training
🎯 Requirements
• Deep understanding of recent architectures and training methodology used for LLMs and foundation models • Experience with pre-training or post-training (SFT, RLHF, DPO, reward modeling, or equivalent) — note, preference will be given to individuals with post-training experience. • Strong grounding in optimization techniques: AdamW variants, LR scheduling, mixed precision, stabilization methods, and scaling behaviors • Strong experimental design skills: ablations, controlled comparisons, scaling experiments • Fluency in PyTorch or JAX for implementing research ideas efficiently • Ability to collaborate effectively with both research-oriented and engineering-oriented colleagues • Ability to turn conceptual research directions into runnable prototypes that integrate into the training system • Familiarity with common tools (Linux command line, git, Docker, …) • Openness to adopting new tooling • Strong written English • Open, honest and transparent communication skills
🏖️ Benefits
• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options
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