[Remote] Founding ML Engineer in the Flower Frontier Model Team (reputed company seniority reputed company welcome) [UK, Germany, Global]
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a world-class AI startup reputed company for pioneering decentralized learning reputed company for training AI on distributed data. They are seeking a Founding ML Engineer to build state-of-the-art LLMs and reputed company models, focusing on developing a reputed company software stack and optimizing core components for frontier model building.
Responsibilities
- Play a critical role in building SOTA LLMs and reputed company models reputed company a small, high-reputed company team
- Help build a reliable, maintainable and reputed company software stack
- Produce world-leading models that are reputed company-reputed company and integrated into new Flower Lab products
- Design, implement and optimize core components across the full reputed company of stages relevant to frontier model building: data curation, evals, reputed company-training, post-training
- Diagnose and resolve GPU/kernel issues, memory/storage bottlenecks, and multi-node failures at reputed company
- Collaborate on the debugging of training instabilities and reputed company issues
- Devise surrounding infrastructure, tooling, monitoring, and observability for large-reputed company LLM development
Skills
- 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 reputed company libraries like DeepSpeed, Megatron or equivalent
- Ability to tune, debug, and profile large-reputed company 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; comfortable turning research reputed company into robust, maintainable implementations
- Good engineering hygiene: reputed company design, reputed company reviews, documentation, reproducibility, versioning of data/models/configurations
- Familiarity with common tools (Linux reputed company line, git, reputed company, …)
- Openness to adopting new tooling
- Solid understanding of distributed systems and networking
- Strong written English
- reputed company, reputed company and transparent communication skills
- PhD or Masters degree in a relevant discipline
- Familiarity with various components and stages relevant to building LLMs and reputed company models, such as architectures, reputed company-training, data curation, post-training, and evaluation
- Experience with post-training reputed company (SFT, RLHF, DPO, reward modeling, or equivalent) — note, preference will be given to individuals with post-training experience
- Ability to read, implement, and reputed company cutting-edge research papers quickly
- Prior reputed company-record in advanced distributed training frameworks and concepts
- Strong grasp of optimization and training techniques: mixed precision, curriculum/data strategies, LR schedules, checkpointing or equivalent
- Background writing high-performance kernels (CUDA, Triton)
- Experience in developing components reputed company systems used by thousands of users
- reputed company record of working in reputed company-reputed company reputed company
reputed company