What’s the Difference Between an AI Engineer and a Machine Learning Engineer?
The main difference between an AI engineer and a machine learning engineer is where they start. An AI engineer builds product features on top of existing models, such as large language models (LLMs). A machine learning engineer designs, trains and tunes the models themselves, then keeps them running in production.
What does an AI engineer do vs. a machine learning engineer?
An AI engineer turns existing models into features your users interact with. A machine learning engineer builds custom models from your own data.
| AI engineer | ML engineer | |
|---|---|---|
| Starts from | Pre-trained models and model APIs | Your own data |
| Builds | RAG pipelines, AI agents and tool use, prompts, evals and guardrails | Training pipelines, features, custom models, retraining jobs |
| Main output | LLM-powered features such as chat, search and agents | Models that predict, classify or recommend inside your product |
| Typical tools | Python, LLM APIs, LangChain, vector databases, eval frameworks | Python, PyTorch or TensorFlow, scikit-learn, MLflow, SageMaker |
| Measured on | Eval scores, feature reliability, cost per request | Model accuracy, training throughput, latency |
| Math and statistics | Moderate | Heavy: statistics, algorithms, model architecture |
The line between the two is blurring. Many AI engineers fine-tune models, and many ML engineers now ship LLM features. When you read a job description or a CV, check whether the work starts from a pre-trained model or from training data. That usually tells you which role it really is.
Who gets paid more, an AI engineer or an ML engineer?
Machine learning engineers get paid more in the US, about $128,800 a year on average versus $101,800 for AI engineers. In Latin America the two roles pay almost the same at every level.
| Salary per year | AI engineer | ML engineer |
|---|---|---|
| US average | $101,800 | $128,800 |
| LatAm, entry level (1–3 yrs) | $40K–$48K | $41K–$50K |
| LatAm, senior (6+ yrs) | $88K–$107K | $91K–$111K |
LatamCent salary estimates for remote roles with US companies in Colombia, Mexico, Brazil and Argentina, 2026. Ranges show the lowest and highest of the four countries.
Should you hire an AI engineer or a machine learning engineer?
Hire an AI engineer if you want to add features like chat, search or agents using existing models. Hire a machine learning engineer if you need a custom model trained on your own data.
- AI engineer if the goal is an LLM-powered feature, such as a support assistant, smarter search or an agent that completes tasks in your product. Speed to launch matters more than a custom model.
- ML engineer if the feature depends on patterns in your own data, such as fraud scoring, churn prediction, forecasting or recommendations. An off-the-shelf model won’t know your data.
- Need both? Start with an AI engineer to ship LLM features quickly, then add an ML engineer once a feature needs a model trained on your own data.
Need someone who can build custom models, not just call an API?
LatamCent hires pre-vetted machine learning engineers in Latin America who work US hours and cost far less than a US hire. You interview a shortlist and make the hire in 21 days or less.
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