I have done quite a few google searches but have not found a clear answer to the following use case. Basically, I would rather use cloud 9 (most of the time) as my IDE rather than Jupyter. What I am confused/not sure about is, how I could executed long running jobs like (Bayesian) hyper parameter optimisation from there. Can I use Sagemaker capabilities? Should I use docker and deploy to ECR (looking for the cheapest-ish option)? Any pointers w.r.t. to this particular issue would be very much appreciated. Thanks.
You could use whatever IDE you choose (including your laptop).
SaegMaker tuning job (example) is asynchronous, so you can safely close your IDE after launching it. You can monitor the job the AWS web console, or with a DescribeHyperParameterTuningJob API call.
You can launch TensorFlow, PyTorch, XGBoost, Scikit-learn, and other popular ML frameworks, using one of the built-in framework containers, avoiding the extra work of bringing your own container.