About the role
Research #AI for Science Required: Master's degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field. Strong familiarity with Linux and the open-source ecosystem. Proficient working with large datasets in a cloud or HPC environment. Proficient in building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. Strong analytical, problem-solving, and communication skills. Passionate about pushing the boundaries of science. Prior experience developing high-performance scientific software is not required, but preferred. Experience with open source machine learning frameworks (e.g., PyTorch, ggml, llama.cpp, vllm) is a plus. Experience with Materials Science (in particular Density Functional theory) is a plus. Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data. Build and optimize distributed data processing and model building pipelines. Develop and maintain tools and technologies for building, training, optimizing, scaling machine learning solutions. Collaborate with cross-functional teams, including scientists, researchers, and software engineers. Document and share best practices across the organization. Maintain the highest standards in code quality and software design.
