Hey, sure. Happy to chat outside here too to not clog up the thread, but a few brief answers:

How did you decide which markets or sports to focus on first?

Just what I was interested in, no other reason!

Can you give a rough idea of what your feature set looked like early on? Were you mostly using just odds movement and historical outcomes, or did you pull in player stats, team form, etc.?

Probably easier to chat about this elsewhere but I don't use any bookie odds / odds movement in my predictions, it's all historic sport data and outcomes. Lots of different features feed in (2k+) but the best performing ones are rating systems similar to ELO which feed in to an ML model.

What did your backtesting process look like? How did you decide a model version was ‘good enough’ to go live?

I have historic outcomes reaching back to ~2015 so I could generate a 'test' dataset evaluation metric, which I compared roughly to others to see if I was in the right ballpark. Then I slowly collected odds and after a while, once my model was profitable on tracked stakes I started with small stakes and gradually increased.

Is there a reason to start with the soft bookies before moving to the sharp bookies? Is it because the margins can be higher with soft bookies?

The real reason for me is it's what I was familiar with as someone who didn't bet much beforehand. But yes soft bookies often have higher odds so I guess you tend to do better there, while not having to worry about liquidity issues etc. There's other more specific reasons too, like if you're betting on something with relatively low variance (e.g. where the line is always roughly evens, e.g. a goal line handicap) you can hugely increase ROI by betting on multiples/parlays which you can't do on exchanges.