Machine Learning Engineer H/F

Hace 4 días

Barcelona, Barcelonés (comarca); Provincia de Barcelona; Cataluña, España Multiverse Computing Jornada completa
Multiverse ComputingMultiverse Computing is a fast-growing deep-tech company founded in ***
* 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.edge AI and quantum technologies.world value for global clients. 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?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.
Required QualificationsMaster'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?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: SFT, DPO, or RL (GRPO, PPO), or frameworks such as verl, TRL or OpenRLHF.
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.source ML projects (PyTorch, Megatron?Knowledge of tensor networks or quantum?Perks & BenefitsIndefinite 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?