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Tools our Machine Learning Engineers work across
How to hire your Machine Learning Engineer
Open your position
Post your role risk-free. You won’t pay until you make a hire.
Review candidates in 48 hours
We match you with senior, vetted candidates who’ve actively expressed interest in your role — interviews, not résumés.
Hire — and keep them
We handle compliance, payments, and equipment. You control comp with our cost-plus model, so your best people stay.
What do Machine Learning Engineers do?
Machine Learning Engineers build and ship the models your product runs on — training pipelines, deployment, and the MLOps that keep models reliable in production. They pair strong software fundamentals with applied ML: feature engineering, model training and evaluation, and serving at scale. They own the full lifecycle, from experiment to production, keeping models accurate and cost-effective as data and usage change.
Core responsibilities
- Build, train, and evaluate machine learning models
- Design feature pipelines and training infrastructure
- Deploy and serve models reliably at scale
- Own MLOps — monitoring, retraining, and performance
- Partner with data and product to ship ML features end to end
Not your traditional staff aug.
Remotely's Transparent Staff Aug
You choose the candidates, and they choose you too
You control compensation and retain the best talent
7,000+ developers analyzed for proven experience
AI-fluent and startup-minded
Speed and visibility powered by a tech-enabled platform
Engineers who stay for the long haul.
Traditional Staff Aug
Developers are assigned, not aligned
The agency controls the paycheck
Limited pool, limited options
Code monkeys with no business sense
Powered by emails & spreadsheets
Here today, gone tomorrow
Machine Learning Engineers in your time zone
Our talent works across Latin America — Brazil, Mexico, Colombia, Argentina, Chile, and beyond — on US business hours. Most of the region sits within a few hours of US Eastern time, so you get a full workday of overlap: standups, pairing, and code review happen in real time, not overnight.
And they communicate like teammates, not vendors — fluent, professional English and a startup-ready working style.
Where they work
Brazil
Mexico
Colombia
Argentina
Chile
+ 12 more
