About FundamentalFundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM)
- purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict.
About FundamentalFundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM)
- purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict.
At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.

Key Responsibilities
Profile end-to-end distributed training runs to identify bottlenecks across compute, GPU memory, and inter-GPU communicationContribute to architectural decisions that improve the efficiency and reliability of large-scale training jobs, including developing Triton/CUDA kernels when neededDesign and implement model scaling,



parallelization, and memory optimization techniques for training workloads with very large context sizesCollaborate closely with ML Researchers to diagnose architectural inefficiencies, ensure new research ideas scale efficiently in practice, and spread internal knowledge about model efficiency and optimizationDrive the productionization and serving of our models from the research side, including improving inference efficiency through techniques such as quantizationMust haveStrong understanding of modern ML architectures and large-scale training pipelinesExperience running distributed training jobs on multi-GPU systemsAdvanced profiling and debugging skills across CPU, GPU, memory usage, latency, and inter-GPU communicationStrong programming skills in PythonExperience with model scaling and parallelization strategies, including tensor and pipeline parallelismNice to haveFamiliarity with NCCL, MPI, and distributed communication primitivesKnowledge of PyTorch and Triton internalsProgramming experience with C++ and CUDABenefitsCompetitive compensation with salary and equityComprehensive health coverage for you and your dependentsPaid parental leave for all new parents, inclusive of adoptive and surrogate journeysRelocation support for employees moving to join the team in one of our office locationsA mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

📌 Senior Applied Research Engineer (Barcelona)
🏢 Fundamental
📍 Barcelona