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.