# Senior Applied Research Engineer at Fundamental > Onsite · Spain · Senior · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3AFundamental%3A9e40b619-8257-4dd9-a9b4-02ccdfd3c6db (read 2026-11-07). ## Facts (observed) - Company: [Fundamental](https://alderhq.app/companies/fundamental) - Location text: Barcelona - Where it can be done from (inferred): Onsite · Spain (evidence: "Location: Barcelona") - Posted: 2026-03-25 (227 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/Fundamental/9e40b619-8257-4dd9-a9b4-02ccdfd3c6db - Skills listed (inferred): Python, C++, PyTorch ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Barcelona, n 5): p25 €85k, median €85k, p75 €138k ## Description (the employer's text) ### About Fundamental Fundamental 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 communication Contribute to architectural decisions that improve the efficiency and reliability of large-scale training jobs, including developing Triton/CUDA kernels when needed Design and implement model scaling, parallelization, and memory optimization 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 spread internal knowledge about model efficiency and optimization Drive the productionization and serving of our models from the research side, including improving inference efficiency through techniques such as quantization ### Must have Strong understanding of modern ML architectures and large-scale training pipelines Experience running distributed training jobs on multi-GPU systems Advanced profiling and debugging skills across CPU, GPU, memory usage, latency, and inter-GPU communication Strong programming skills in Python Experience with model scaling and parallelization 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 Comprehensive health coverage for you and your dependents Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys Relocation support for employees moving to join the team in one of our office locations A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3AFundamental%3A9e40b619-8257-4dd9-a9b4-02ccdfd3c6db and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.