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Senior LLM Engineer

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Develop and optimize Large Language Models (LLMs) across their full lifecycle. Train, compress, and evaluate models, contributing to research and open-source releases. Requires Master's/PhD or equivalent, 4+ years of experience with PyTorch and distributed training.

Key Highlights
Senior LLM Engineer role in a deep-tech company.
Focus on full model lifecycle: data, training, compression, evaluation, inference.
Requires strong PyTorch, distributed training, and post-training experience.
Key Responsibilities
Train and post-train LLMs and multimodal models
Design compression techniques
Build RL environments
Research and prototype post-transformer and hybrid architectures
Build data pipelines
Design rigorous ablations and evaluations
Port and optimise models for inference
Write up experiments and results
Review code, mentor teammates
Technical Skills Required
PyTorch Distributed Training LLM Post-training
Benefits & Perks
Advanced relocation package
Language courses
Visa services
Signing bonus
Relocation bonus
Nice to Have
NVIDIA stack experience
RL infrastructure
Model compression techniques
Post-transformer architectures
Physical AI
Multimodal model training
Inference on alternative hardware
Large-scale data processing
Evaluation tooling
Publications at top venues
Spanish language

Job Description

We are looking for a Senior LLM Engineer to join our Research team. You will work across the full model lifecycle: data, distributed training, post-training, compression, evaluation and efficient inference. Our past work includes compressing and healing open-weight models, post-training with SFT, RL and distillation, multimodal training, knowledge editing, and building our own family of models. Priorities change quickly in research, so we value strong fundamentals over narrow specialisation. When it makes sense, we publish papers and release models and code.

As an LLM Engineer, you will

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