ONNX is a standardized format used to represent ML models: https://onnx.ai/
Popular ML frameworks provide support for ONNX via convertors: https://github.com/onnx/onnxmltools/tree/master/onnxmltools/convert (XGBoost, Spark).
The goal of this task is to create a convertor from H2O GBM MOJO to ONNX representation. Inspiration could be taken from XGBoost implementation of the convertor: https://github.com/onnx/onnxmltools/tree/master/onnxmltools/convert/xgboost
Not all distributions / objective functions needs to be supported on Day 1 (XGBoost doesn't support Tweedie for example). Main challenge will be most likely to handle categorical encoding. For initial POC it is also okay to do just 1-hot encoded models.