Hire a Machine Learning Engineer from Latin America
Pre-vetted ML Engineers who build and deploy production models — for 50-60% less than US rates.
Salary Comparison
| Level | US Rate | LATAM Rate | Savings |
|---|---|---|---|
| Junior (1-3 yrs) | $8,000/mo | $3,500/mo | 56% |
| Mid-Level (3-5 yrs) | $12,000/mo | $5,500/mo | 54% |
| Senior (5+ yrs) | $15,000/mo | $7,000/mo | 53% |
Key Skills
Our Vetting Process
Only the top 3% of applicants pass.
Technical Assessment
ML system design, model evaluation challenges, and coding exercises in Python.
English Proficiency
Conversational English evaluation to ensure effective communication with research and product teams.
Cultural Fit
Behavioral interviews assessing research rigor, production mindset, and remote collaboration skills.
Reference Checks
Verification of deployed models, published research or patents, and professional references.
Hiring Timeline
Tell Us What You Need
1 dayShare your ML use case, tech stack, model requirements, and seniority needs.
Review Pre-Vetted Candidates
7-14 daysWe present 3-5 ML engineers with relevant domain and framework experience.
Start Working Together
Day 21Onboard your new ML Engineer. We handle contracts, payroll, and compliance if needed.
Pricing Plans
Starting from $3500/month
Placement
We source and vet ML engineers. You interview top candidates and manage them directly.
- Sourcing & vetting
- Technical assessments
- English proficiency tests
- Candidate shortlist (3-5)
Staffing
Full-service: hiring, onboarding, payroll, and compliance handled by Nexus.
- Everything in Placement
- Onboarding support
- Payroll management
- Compliance & contracts
Teams
Build an ML team with research, engineering, and MLOps capabilities.
- Everything in Staffing
- Team coordination
- Performance tracking
- Scalable on demand
Frequently Asked Questions
How much does a Machine Learning Engineer cost in Latin America?+
LATAM ML Engineers cost $3,500-$7,000/month depending on seniority, versus $8,000-$15,000/month in the US. Savings of 53-56%.
Can your ML Engineers deploy models to production?+
Yes. Our engineers have experience with full MLOps pipelines — from training to deployment using SageMaker, Vertex AI, and custom Kubernetes setups.
Do you have specialists in NLP or computer vision?+
We have ML Engineers with deep expertise in NLP (LLMs, transformers, text classification), computer vision, and recommendation systems. We match to your domain.
How quickly can I hire an ML Engineer?+
Average time-to-hire is 21 days. We present pre-vetted candidates within 7-14 days.
Ready to Hire a Machine Learning Engineer?
Tell us what you need and we'll present top candidates within 7-14 days.