AWS · Professional Certification · Associate
AWS Certified Machine Learning Engineer – Associate
Crydd Score 70
Demand High
Career Value High
Recognition High
AWS ML Engineer at a glance
- Provider
- AWS
- Credential type
- Professional Certification
- Exam required
- Yes
- Category
- Machine Learning
- Level
- Associate
- Cost
- $150
- Difficulty
- Advanced
- Time to earn
- 2–4 months
- Validity
- 3 years
- Format
- MLA-C01: 65 questions, 130 minutes (English until 28 September 2026). Updated MLA-C02, in beta: 85 questions, 170 minutes, $75 during the beta
- Prerequisites
- None required; ML and AWS experience recommended
What is AWS ML Engineer?
AWS's associate certification for machine learning engineers: preparing data, developing models, deploying and orchestrating ML workflows, and monitoring, maintaining and securing ML solutions, largely with Amazon SageMaker AI.
Skills it covers
- ML pipelines on AWS
- Model deployment
- MLOps basics
- Data preparation
Is AWS ML Engineer worth it? The Crydd Verdict
CS 70Choose it if
You build and run machine learning systems on AWS, or are moving from data science into MLOps.
Consider alternatives if
You are new to AI on AWS: the AI Practitioner first. For generative AI applications rather than classic machine learning, the AWS Certified Generative AI Developer – Professional.
Why we say so
It is AWS's main machine learning engineering certification and tests the production skills teams hire for.
Market demand
Machine learning engineer and MLOps roles are in high demand, and AWS experience with SageMaker is frequently requested; an updated exam, MLA-C02, is in beta.
Where AWS ML Engineer takes you
- Machine Learning Engineer
- Data Scientist
Career roadmaps show where this certification fits in each path. See the roadmaps.
Related certifications
Curated connections from the catalog — each labelled with how it relates to AWS ML Engineer, so you know why it’s here.
Careers AWS ML Engineer leads to
The professional paths this certification genuinely serves — browse every relevant credential for each.
A sensible order
Where AWS ML Engineer sits on the path — build up, then step on.
Build the foundation first
Earlier steps on the same path
