Multiverse Computing is a fast-growing deep-tech company founded in 2019 and recognized by CB Insights as one of the 100 most promising AI companies globally. We are the largest quantum software company in the EU, with 300+ employees worldwide and growing, delivering advanced solutions trusted by leading global enterprises across several critical industries, including finance, energy, manufacturing, telecom, and industrial sectors. Our mission is to enable organizations to gain a meaningful competitive edge through cutting-edge AI and quantum technologies. You’ll work alongside world-leading experts, developing solutions that deliver real-world value for general clients. We are committed to fostering an inclusive, ethics-driven culture grounded in sustainability, diversity, and collaboration — a place where ambitious, curious people take ownership, push boundaries, and grow. As a Machine Learning Engineer, you will: Build and maintain the training stack our researchers use every day: multi-node training and post-training pipelines (SFT, distillation, RL) built on Megatron-LM, Megatron Bridge and NeMo RL. Build scalable data pipelines for curation, filtering, deduplication, tokenization and synthetic data generation. Profile and optimise training and inference: Turn research ideas (new architectures, compression methods, training recipes) into clean, tested, reusable code, and run experiments together with the research team. Master’s in Computer Science, AI, Mathematics, Physics, Engineering or a related field, or equivalent industry experience.



~Strong Python software engineering: clean, maintainable, tested code; git, code review, unit and integration tests, CI. ~ Strong PyTorch and hands-on experience training or fine-tuning transformer models. ~ Experience running multi-GPU jobs and a working understanding of distributed training (data, tensor and pipeline parallelism; Comfortable with Linux, containers (Docker or similar) and shared GPU clusters (Slurm or Kubernetes). ~ Experience building data pipelines that process large datasets. ~ Solid ML fundamentals: you understand what happens inside training, not just how to launch it. ~ Fluent English. Hands-on post-training: Inference engines (vLLM, SGLang, TensorRT-LLM) for serving, synthetic data generation or RL rollouts. Deployment on edge or alternative hardware: llama.
GPU performance work: profiling (Nsight, PyTorch profiler), Triton or CUDA kernels. Experiment tracking and MLOps (MLflow, Weights & Biases), cloud platforms (ideally AWS). Spanish. Merged contributions to major open-source ML projects (PyTorch, Megatron-LM, vLLM, Hugging Face, etc.). Knowledge of tensor networks or quantum-inspired methods. Indefinite contract. Variable performance bonus.

We offer
work visa sponsorship (if applicable). Relocation package (if applicable). Private health insurance. Eligibility for educational budget according to internal policy. Hybrid opportunity. Flexible

working hours
. A high-performance, collaborative environment, operating at pace on cutting-edge technologies.

📌 Machine Learning Engineer, hibrido (España)
🏢 Multiverse Computing
📍 España