Senior Research Engineer Machine Learning, AI for Science

Develop and maintain tools, models and technologies for building, training, optimizing and scaling machine learning solutions. 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. Prepare and maintain open-source releases and releases for internal and external beta testers. Work cross-functionally with machine learning researchers, engineers and researchers from the natural sciences. Maintain high standards in code quality and software design. Document and share best practices across the organization. Completed MSc in computer science, machine learning, AI or a related area. Proficiency in collaborative software engineering in Python. Familiarity with Linux and the open-source ecosystem. In-depth understanding of open-source machine learning frameworks such as PyTorch and/or Jax. Experience in designing, developing and deploying ML systems. Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds. PhD degree in computer science, machine learning, AI or a related field, or comparable industry experience in working with machine learning and large datasets. Experience working with major cloud platforms and/or HPC. Experience with LLMs and/or frameworks like ggml, llama.cpp, vllm Research #AI for Science This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. *