These roles overlap, but they are not identical. Picking the wrong role target can send you into the wrong certification and project queue for months.
Practice free at dotCreds.com, then choose your next certification based on the AI lane you actually want.
Choose the work style you want to do every week.
AI engineers often own service integration, API pipelines, app-level deployment, monitoring, and business use-case delivery. AI-102 is usually the strongest cert fit here.
ML engineers spend more time on model behavior, training/evaluation constraints, data quality, and productionization patterns. Google ML Engineer is a closer alignment than general AI fundamentals alone.
GenAI developers focus on LLM prompting patterns, retrieval pipelines, agent behavior, and user-facing generative experiences. Google Generative AI Leader is a useful context cert, often paired with hands-on app projects.
If you are not sure yet, start with the AI Career Hub, choose one lane, and run one cert plus one project cycle before switching directions.
Use one lane, one next cert, and one practice page at a time. That is usually faster than trying to collect every AI cert at once.