Founding ML Engineer, Flower Frontier Model Team

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🕒 December 17, 2025

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Flower Labs

WebsiteLinkedInAll Job Openings

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

• Join as a founding member of the Flower Frontier Model Team • Build category-defining models that blend existing practices with decentralized learning methods • Help build a reliable, maintainable and scalable software stack • Produce world-leading open-sourced models integrated into new Flower Lab products • Design, implement and optimize core components across data curation, evals, pre-training, post-training • Diagnose and resolve GPU/kernel issues, memory/storage bottlenecks, and multi-node failures at scale • Collaborate on the debugging of training instabilities and related issues • Devise surrounding infrastructure, tooling, monitoring, and observability

🎯 Requirements

• Exceptional software engineering skills (Python, deep learning frameworks, testing, profiling, refactoring, reproducibility) • Expertise with modern ML training stacks: PyTorch, JAX or equivalent • Experience implementing model architectures from scratch and working within libraries like DeepSpeed, Megatron or equivalent • Ability to tune, debug, and profile large-scale training runs • Hands-on experience working with large GPU clusters, including job orchestration, scheduling, multi-node runs, NCCL/RDMA issues, and GPU performance optimization • Ability to collaborate effectively with both research-oriented and engineering-oriented colleagues • Good engineering hygiene: modular design, code reviews, documentation, reproducibility, versioning of data/models/configurations • Familiarity with common tools (Linux command line, git, Docker) • Openness to adopting new tooling • Solid understanding of distributed systems and networking • Strong written English • Open, honest and transparent communication skills

🏖️ Benefits

• Opportunity to work on frontier AI models • Potential for technical leadership • Collaborative start-up environment