Founding Research Engineer – Flower Frontier Model Team
Flower Labs
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇪🇺 Anywhere in Europe
Visit company websiteJob Level
Senior
Tech Stack
DockerLinuxPyTorch
About the role
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
LLMsfoundation modelspre-trainingpost-trainingSFTRLHFDPOreward modelingoptimization techniquesexperimental design
Soft skills
collaborationcommunicationconceptual researchtransparencyopenness