Senior LLM Engineer: Lead AI/Quantum Model Research

Relocate; Barcelona; Presencial; EUR 110.000 - 160.000; Tempo integral

Resumo da vaga

Multiverse Computing is seeking a Senior LLM Engineer to join our Research team in Barcelona. You will oversee the full model lifecycle: data handling, distributed training, post-training, compression, evaluation and efficient inference.

Our work includes compressing and healing open-weight models, SFT, RL and distillation across multimodal data, and building our own model family. You will collaborate with world‑leading researchers to publish papers and release code when appropriate.

Qualificações

• Master’s or PhD in Computer Science, AI, Mathematics or Physics, or equivalent industry experience.
• Senior: 4+ years of hands-on experience training or post-training transformer models.
• Strong PyTorch; comfortable with model code and parallelism.
• Experience with distributed training on multi-node clusters with Slurm/K8s.
• Hands-on post-training experience: SFT, DPO, and at least one RL method (PPO, GRPO or similar).
• Solid mathematical foundations in linear algebra, optimisation and probability.
• Good understanding of GPU fundamentals; memory hierarchy, mixed precision, profiling.
• Fluent English.

Responsabilidades

• Train and post-train LLMs and multimodal models on multi-node GPU clusters using SFT, preference optimisation, RL (e.g. GRPO), and on-policy and offline distillation.
• Design compression techniques (quantization, pruning, quantization-aware training, quantum-inspired tensor-network methods) and healing recipes that recover the quality of compressed models.
• Build RL environments, reward functions and verifiers for reasoning, coding and agentic tasks, and extend RL methods to world models and Physical AI.
• Research and prototype post-transformer and hybrid architectures (state-space models, linear attention, MoE), from small-scale ablations to scaling recipes.
• Build data pipelines for curation, filtering, deduplication and large-scale synthetic data generation.
• Design rigorous ablations and evaluations on current benchmark suites (reasoning, coding, long-context, instruction following, agentic) as well as internal evals.
• Port and optimise models for inference on various accelerators and edge chips, profiling latency, memory and throughput.
• Write up experiments and results as internal reports and, where relevant, papers and open-source releases.
• Review code, mentor teammates, and follow and bring in the latest research.

Conhecimentos

PyTorch

Distributed training

SFT

RL methods

Quantization

Model compression

Formação

Master's or PhD in CS/AI/Math/Physics

Equivalent industry experience

Descrição da vaga

Multiverse Computing is seeking a Senior LLM Engineer to join our Research team in Barcelona. You will oversee the full model lifecycle: data handling, distributed training, post-training, compression, evaluation and efficient inference.

Our work includes compressing and healing open-weight models, SFT, RL and distillation across multimodal data, and building our own model family. You will collaborate with world‑leading researchers to publish papers and release code when appropriate.