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Senior Applied Research Engineer | Barcelona | Up to €150k

Barcelona, Spain

Apply by 16 May 2026

€85000 - €150000 per annum

Job Ref.: BH-57191

Job Type: Permanent

Job Description

Senior Applied Research Engineer | Barcelona, Spain

We are partnered with a cutting-edge AI company shaping the future of enterprise decision-making. Founded by experienced technologists from leading research environments, the firm has developed a market-leading platform purpose-built for the structured data that underpins critical business decisions. Backed by top-tier investors and trusted by some of the world’s largest organisations, the company helps enterprises unlock significant value by enabling more accurate, forward-looking decision-making.
  You will work on novel technical challenges in large-scale model development and contribute to technology that is changing how major organisations operate. This is an opportunity to join a category-defining company at an early stage and help shape its trajectory. Location & compensation
  • Location: Barcelona, Spain, Hybrid working 
  • Salary: Up to €150,000 (plus equity)
  • Industry: Technology
Key responsibilities
  • Profile end-to-end distributed training runs to identify bottlenecks across compute, GPU memory, and inter-GPU communication.
  • Influence architectural decisions to improve efficiency and reliability of large-scale training jobs, including developing Triton/CUDA kernels when needed.
  • Design and implement model scaling, parallelisation, and memory optimisation techniques for training workloads with very large context sizes.
  • Collaborate closely with ML Researchers to diagnose architectural inefficiencies, ensure new research ideas scale efficiently in practice, and share internal knowledge on optimisation.
  • Drive productionisation and serving of models from the research side, including improving inference efficiency via techniques such as quantisation.
Must have
  • Strong understanding of modern ML architectures and large-scale training pipelines.
  • Hands-on experience running distributed training jobs on multi-GPU systems.
  • Advanced profiling and debugging across CPU, GPU, memory usage, latency, and inter-GPU communication.
  • Strong programming skills in Python.
  • Experience with model scaling and parallelisation strategies, including tensor and pipeline parallelism.
Nice to have
  • Familiarity with NCCL, MPI, and distributed communication primitives.
  • Knowledge of PyTorch and Triton internals.
  • Programming experience with C and CUDA.
Benefits
  • Competitive compensation with salary and equity and comprehensive benefits
  • Relocation support for employees moving to join the team in an office location.
  • A mission-driven, low-ego culture valuing diversity of thought, ownership, and bias towards action.
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