Hire Machine Learning Engineers
Pre-Vetted Machine Learning Engineers From Latin America, Working US Hours
Hire full-time machine learning engineers and ML developers from Latin America. Pre-vetted, fluent in English and working US hours, hired in 21 days at about 60% less than US salaries.
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30-minute strategy call + interview plan. No commitment.★★★★★ 5.0 on G2
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Why Hire Machine Learning Engineers From Latin America?
US SaaS companies hire machine learning engineers in Latin America for three reasons.
Same working hours. Engineers in Colombia, Mexico, Panama and Guatemala share or sit close to US Eastern and Central time, and Brazil is only one to two hours ahead. Your ML engineer joins standups, code reviews and incident calls live, not the next morning.
Lower cost without dropping seniority. The average machine learning engineer in Latin America earns about $54K a year versus $135K in the US. That gap lets you hire a senior engineer for less than a junior US salary, or add two engineers for the cost of one.
Production experience. Our candidates have shipped models into real products: recommendation systems, NLP pipelines, computer vision features and MLOps platforms. They work in the same stack your team uses, from PyTorch and TensorFlow to MLflow, Airflow and AWS SageMaker.
Engineering Teams That Hired Through LatamCent
Real results from engineering hires in Latin America.
An engineering org built in Brazil at 63% below US cost, with 88% retention.
Read the storyA senior Python developer raised the bar on quality. Work that took multiple sprints started happening in one.
Read the storyThe AWS Premier Tier Partner added engineers with AI/ML, AWS and Azure backgrounds to work with its US teams in real time.
Read the storyLatamCent
Can Help You
Hire Machine Learning Engineers in 21 Days
We place vetted Machine Learning Engineers experienced in building LLM applications, AI agents, NLP solutions, computer vision systems, and production-ready ML models.
Payroll & IP Compliance
We handle international payroll, tax documentation, and IP transfer under legally binding agreements aligned with U.S. standards.
Fluent English, AI/ML Specialists
All candidates speak fluent English and have experience working in agile teams, deploying AI solutions, training and fine-tuning models, and maintaining production-grade ML systems.
Get Pre-Vetted Machine Learning Engineers
Looking for AI, ML, LLM, or MLOps engineers? We'll send pre-vetted candidates matched to your tech stack and hiring needs.
30-minute strategy call + interview plan. No commitment.
Responsibilities Of Machine Learning Engineers In SaaS Companies
Model Development & Training
Designs, trains, and iterates machine learning models using production data, balancing accuracy, latency, and cost while aligning model behavior with real SaaS product and business requirements.
Data Pipeline & Feature Engineering
Builds and maintains data pipelines, defines feature stores, and ensures training and inference data remain consistent, reliable, and versioned across environments as products scale and data volume grows.
Model Deployment & Monitoring
Deploys models into production systems, monitors performance drift, latency, and failures, and retrains models as usage patterns evolve to maintain reliability within live SaaS applications.
Cross-Functional Collaboration
Works closely with product, engineering, and data teams to translate business problems into machine learning solutions that integrate cleanly into SaaS workflows and support measurable product outcomes.
Our Candidates Are Experienced Machine Learning Engineers
LatamCent candidates are skillful professionals with excellent English proficiency and impressive work experience.
Junior Machine Learning Engineer
With 0-2 years of experience, this role focuses on preparing and organizing data for machine learning tasks. Junior engineers assist in building and testing models under guidance, learning essential skills while contributing to team efforts.
Mid-Level Machine Learning Engineer
Typically bringing 2-5 years of experience, mid-level engineers refine machine learning models to solve practical challenges. They test and improve performance while collaborating with teams to ensure reliable solutions.
Senior Machine Learning Engineer
Requiring 5-8 years of experience, senior engineers take charge of designing scalable models and guiding their deployment. They address complex problems, mentor junior colleagues, and ensure quality across projects. This role demands expertise and collaboration.
Director of Machine Learning
With 8+ years of experience, directors lead the strategic vision for machine learning initiatives. From managing teams to aligning goals with business priorities, they oversee development. Their role ensures methodologies are effective while inspiring improvement.
30-minute strategy call + interview plan. No commitment.
Machine Learning Engineer Cost: Latin America vs. USA
A machine learning engineer in the US costs about $135,000 a year in salary alone. The same role in Latin America averages about $54,000, a saving of roughly $81,000 per hire, or around 60%.
Put another way, that is about $26 an hour in salary-equivalent cost versus $65 in the US. For a team of three ML engineers, the difference is close to $250,000 a year that can go back into runway, compute or more hires.
Seniority and specialty change the number. Senior engineers and specialists in LLMs, MLOps or computer vision earn more than the average, so treat these figures as a baseline and ask us for a range for your exact role.
Salary Comparison for Machine Learning Engineers
This is an average based on the top 50% of salaries in the region. Top 10% earners usually have higher rates.
How to Hire Machine Learning Engineers in 21 Days
Kickoff & Search
Sign the agreement, pay the retainer, and your recruitment begins. Our Talent Partners dive into the market to headhunt 1,100–1,700 qualified Machine Learning Engineers who meet your job requirements and timezone preferences.
Screening & Evaluation
Our Talent Partners will thoroughly vet candidates through English language tests, personality assessments, and tech capability checks. We conduct interviews to evaluate past work, communication skills, and set expectations.
Selection & Onboarding
You'll assess the top candidates and decide who's right for your team. Once selected, we handle reference checks, legal agreements, and onboarding to payroll. Your new Machine Learning Engineer is now ready to contribute and integrated into your team.
30-minute strategy call + interview plan. No commitment.
Monarch's CTO on hiring an engineering manager in Brazil
What Engineering Leaders Say
“I always say there’s no Steve Jobs without Steve Wozniak, and that’s what this hire became for us. Without LatamCent, there’s no app.”
Evan LeaphartCEO, Kredit Academy“Our main goal right now is to stay profitable while growing 50% year over year. LatamCent has been part of making that possible.”
Travis MarieaCEO, FlxpointMachine Learning Engineers for hire: Sample Profiles
Every Machine Learning Engineer in our roster has been individually screened for technical depth, English fluency, and real project experience. You will find specialists across different sub-disciplines and seniority levels, all based in Latin America, working in US time zones, and available for full-time dedicated roles.
Deep Learning & Neural Networks Engineer
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“After a difficult job search with recruiters sending mismatched roles, working with LatamCent felt completely different.”
Frequently Asked Questions About Machine Learning Engineers
Book a 30-minute call and share the role, tech stack and time zone you need. Our Talent Partners source and screen machine learning engineers in Latin America, test their English and technical skills, and interview them on past work. You interview the shortlist and pick your hire. We then handle reference checks, the legal agreement and payroll onboarding. Most roles are filled in 21 days or less.
The average machine learning engineer salary in Latin America is about $54,000 a year, compared with about $135,000 in the US. That is roughly $81,000 in savings per hire, or around 60% less. Salary-equivalent hourly cost is about $26 per hour versus $65 in the US. Senior engineers and specialists in LLMs, MLOps or computer vision earn more, so expect a range rather than a fixed rate.
With LatamCent, most machine learning engineers are hired in 21 days or less, from kickoff to signed offer. Hiring the same role in the US often takes several months. The timeline depends on how specific your requirements are and how quickly your team schedules interviews.
Yes. Our machine learning developers live in Latin America, in countries such as Colombia, Brazil, Mexico, Panama and Guatemala, which share or sit within a few hours of US time zones. They join your standups, code reviews and planning meetings in real time instead of handing work off overnight.
They are full-time, dedicated hires. Each machine learning engineer works only for your company, joins your tools and rituals, and stays on your team long term. This is different from freelance marketplaces, where developers often split time across several clients.
Yes. We handle international payroll, tax documentation and IP transfer under legally binding agreements aligned with US standards. You do not need to open a legal entity in Latin America to hire a machine learning engineer there.
A data scientist explores data, runs experiments and builds models to answer business questions. A machine learning engineer takes models into production: building data pipelines, deploying and scaling models, and monitoring them once they are live. If you need a model running inside your SaaS product, hire a machine learning engineer.
Most of our candidates work daily in Python with PyTorch, TensorFlow and scikit-learn. Depending on the specialty, they also use Hugging Face Transformers, spaCy and the OpenAI API for NLP and LLM work, OpenCV and YOLO for computer vision, and MLflow, Kubeflow, Airflow, Docker and AWS SageMaker for MLOps.
Yes. Besides generalist machine learning engineers, we place specialists in MLOps, natural language processing, computer vision, deep learning, generative AI and LLM development. Tell us the specialty and stack on your kickoff call and we will source candidates who have shipped that kind of work.
Discover More AI/ML Talent In Latam
LatamCent helps companies hire pre-vetted, full-time AI and machine learning engineers across specialized roles, including MLOps, computer vision, NLP, generative AI, deep learning, and data science. Explore more related hiring options below.
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LatamCent made hiring engineers simple.
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