AWS ML Engineer Associate case studies
AWS ML Engineer Associate · Put your knowledge to work in context.
The AWS Certified Machine Learning Engineer – Associate (MLA-C01) is a role-based credential for engineers who build, deploy, and operate ML workloads on AWS rather than for researchers who design novel algorithms. It suits data engineers, MLOps engineers, and software engineers who already work with services such as SageMaker, Glue, and Lambda and want formal recognition of production ML skills. The exam is organized around four domains: data preparation for machine learning (28%), ML model development (26%), deployment and orchestration of ML workflows (22%), and monitoring, maintenance, and security (24%). Questions test practical judgment - which storage format fits a training pipeline, how to automate retraining, how to detect model drift, how to secure endpoints and data - more than mathematical derivation. The AWS ML Engineer Associate case studies are 4 cases and about 2,289 words.
1Feature Store Backfill for a Fraud Model
A fraud team trains a gradient-boosted model on 14 months of transaction data stored in Amazon S3. Offline features are computed nightly with a SageMaker Processing job and written to a feature group in SageMaker Feature Store.
593 words, about 3 min2Right-Sizing a Training Job Under a Budget Cap
A team must fine-tune a 7-billion-parameter language model for document classification. They have 40,000 labeled examples averaging 900 tokens, a hard budget of 300 USD, and a two-week deadline.
600 words, about 3 min3Blue/Green Rollout of a Recommender Endpoint
A retail team runs a product recommender behind a SageMaker real-time endpoint serving 4,000 requests per second at peak. A new model version improves offline NDCG by 3 points but changes the response schema: it adds two fields and renames one.
546 words, about 3 min4Detecting Silent Drift in a Demand Forecast
A logistics company forecasts daily package volume per region to staff sortation centers. The model is a gradient-boosted regressor retrained monthly on two years of history.
550 words, about 3 min