Research Engineer

About the Role Join an AI research team as a Research Engineer, turning experimental code into production-ready systems. You will build the shared infrastructure and post-training pipelines that help research projects scale while preserving experimental integrity. What You'll Do Turn research prototypes into tested, reusable data generation, training, and evaluation pipelines. Build distributed experiment infrastructure for data loading, checkpointing, and collecting agent interactions. Profile workloads and improve GPU utilization, memory efficiency, and data throughput. Develop tests, experiment tracking, and debugging tools while ensuring changes preserve research results. Work with researchers to translate ideas into robust, maintainable software. What We're Looking For Strong Python skills and hands-on experience with PyTorch, JAX, or a comparable machine learning framework. Experience building and debugging software for model training, inference, or large-scale data processing. Understanding of machine learning experiments and how data, numerical precision, and implementation choices affect results. Sound software engineering practices, including testing, profiling, version control, and documentation. Distributed training or data processing experience with tools such as PyTorch distributed, DeepSpeed, or Ray is valuable. Familiarity with model-serving, machine learning, or experiment tracking tools is a plus; reinforcement learning systems and multimodal datasets are also useful. Compensation & Benefits Equity is provided. Visa sponsorship is available. Location On-site in Zurich, Switzerland. San Francisco, California is also listed as a work location.