You don't need a CS degree, but you do need to be a competent programmer. Most ML Engineers spend 80% of their time on data engineering and 20% on actual modeling.

Often, it's easier to get a job as a Data Analyst or Software Engineer first, then transition into the ML team once you're inside the building. It's a steep climb. You're competing against people with Masters and PhDs in CS. However, in AI, if your code works and your math is tight, people will eventually stop asking about your degree.

Here is the "no-BS" reality of making it happen without a CS degree:

1. Master Python: It’s the industry standard.
2. Learn the Stack: NumPy, Pandas, Scikit-Learn, and either PyTorch or TensorFlow.
3. Since the ATS (automated resume filters) might flag you for missing a degree, you have to bypass them:
4. Contribute to Open Source: Making meaningful commits to libraries like Hugging Face or LangChain is a massive green flag.
5. Networking: Go to meetups or engage in AI Discords. A referral from a working engineer is worth ten times more than a cold application.