h3About the Role /h3pJoin 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. /ph3What You'll Do /h3ulliTurn research prototypes into tested, reusable data generation, training, and evaluation pipelines. /liliBuild distributed experiment infrastructure for data loading, checkpointing, and collecting agent interactions. /liliProfile workloads and improve GPU utilization, memory efficiency, and data throughput. /liliDevelop tests, experiment tracking, and debugging tools while ensuring changes preserve research results. /liliWork with researchers to translate ideas into robust, maintainable software. /li /ulh3What We're Looking For /h3ulliStrong Python skills and hands-on experience with PyTorch, JAX, or a comparable machine learning framework. /liliExperience building and debugging software for model training, inference, or large-scale data processing. /liliUnderstanding of machine learning experiments and how data, numerical precision, and implementation choices affect results. /liliSound software engineering practices, including testing, profiling, version control, and documentation. /liliDistributed training or data processing experience with tools such as PyTorch distributed, DeepSpeed, or Ray is valuable. /liliFamiliarity with model-serving, machine learning, or experiment tracking tools is a plus; reinforcement learning systems and multimodal datasets are also useful. /li /ulh3Compensation Benefits /h3pEquity is provided. Visa sponsorship is available. /ph3Location /h3pOn-site in Zurich, Switzerland. San Francisco, California is also listed as a work location. /p #J-18808-Ljbffr
