AI Research Engineer – Pre-training, LLM, Multi-Modal

This is a fully remote position, open to applicants in Spain.

📋 Description

• Facilitate foundational pre-training for LLMs and Multi-Modal models on extensive, distributed servers featuring multi-node setups and thousands of NVIDIA GPUs.

• Create, prototype, and expand innovative architectures, tokenizers, and cross-modal alignment layers.

• Source, filter, and curate extensive textual and multi-modal datasets.

• Execute experiments both independently and collaboratively, analyze results, and refine training methodologies to achieve optimal performance.

• Investigate, debug, and resolve bottlenecks affecting model efficiency and stability during training sessions.

• Contribute to the enhancement of distributed training systems to promote scalability and hardware efficiency.

⛳️ Requirements

• A degree in Computer Science or a related discipline.

• Preference for a PhD in NLP, Machine Learning, or a related area, supported by a strong record in AI R&D (including notable publications in A* conferences).

• Practical experience in contributing to large-scale LLM or Multi-Modal pre-training operations on extensive, distributed servers equipped with thousands of NVIDIA GPUs.

• Familiarity and hands-on experience with large-scale, distributed training frameworks, libraries, and tools.

• Profound understanding of cutting-edge transformer and non-transformer modifications aimed at improving intelligence, efficiency, and scalability.

• Strong proficiency in PyTorch and Hugging Face libraries, with hands-on experience in model development, continuous pretraining, and deployment.

🏝️ Benefits

• Health insurance

• Remote work options