Senior LLM Engineer — Quantum AI & Multimodal Training

Relocate.me; Barcelona; On-site; EUR 110,000 - 140,000; Full time

Benefits offered by this job

Advanced relocation package

Language courses

Visa services

Signing bonus

Relocation bonus

Job summary

Multiverse Computing in Barcelona seeks a Senior LLM Engineer to join the Research team, working across data, training, compression and evaluation for large language models and multimodal systems.

The role emphasizes strong fundamentals, distributed training on multi-node clusters, and publishing papers when possible. It offers an advanced relocation package, visa services, language courses and signing bonuses.

Qualifications

• Master’s or PhD in Computer Science, AI, Mathematics, Physics or a related field, or equivalent industry experience.
• Senior: 4+ years of hands-on experience training or post-training transformer models.
• Strong PyTorch. You are comfortable working below library level: model code, custom losses, parallelism configuration.
• Experience with distributed training (FSDP, DeepSpeed or Megatron-LM; data, tensor, pipeline and expert parallelism) 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, and an understanding of training dynamics.
• Good understanding of GPU fundamentals: memory hierarchy, mixed precision, profiling, throughput.
• Rigorous experimental practice: ablation design, reproducibility, experiment tracking, noise-aware evaluation.
• Fluent English.

Responsibilities

• 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.

Skills

PyTorch

Distributed training

RL fine-tuning

SFT / DPO

Linear algebra

Education

Master’s or PhD in CS/AI/Math/Physics or related field

Tools

Slurm

K8s

Megatron-LM

DeepSpeed

NVIDIA stack

Job description

Multiverse Computing in Barcelona seeks a Senior LLM Engineer to join the Research team, working across data, training, compression and evaluation for large language models and multimodal systems.

The role emphasizes strong fundamentals, distributed training on multi-node clusters, and publishing papers when possible. It offers an advanced relocation package, visa services, language courses and signing bonuses.