The algorithms, evaluation practices, and engineering discipline behind building and shipping models.
Keeping ML models running correctly in production: versioning, retraining, monitoring, and serving infrastructure.
Core ML concepts interviewers probe for: model families, evaluation, and the training practices behind them.
Covered under: Machine Learning Engineer
