Hi - yes, of course you can create a Watch for any ML job - it only requires a little knowledge of how watcher works and how to get the information about the anomalies out of either the ML results API or via querying of the
If you're not familiar with how Watcher works with ML you can first take a look at this blog. Although it is a little outdated, the fundamentals are still relevant.
Additionally, it is also good to understand how anomalies are scored and their different flavors (bucket, record, influencer). For info on that, please consult this blog.
I don't quite understand your specific use case and what you're looking for. Perhaps you can more succinctly describe what you want to accomplish and what your current ML job config is.