Overview
ABOUT THE ROLE
Full job description
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.
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