Machine Learning Engineers for Hire
in LATAM
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Machine Learning Engineers for Hire
Julio B.
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SPECIALIZATION
YEARS OF EXPERIENCE
LOCAtion
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Alexis C.
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SPECIALIZATION
YEARS OF EXPERIENCE
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Brenda H.
main skills
SPECIALIZATION
YEARS OF EXPERIENCE
LOCAtion
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Cynthia G.
main skills
SPECIALIZATION
YEARS OF EXPERIENCE
LOCAtion
SALARY EXPECTATIONs
Camilo A
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SPECIALIZATION
YEARS OF EXPERIENCE
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Natalia M.
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SPECIALIZATION
YEARS OF EXPERIENCE
LOCAtion
SALARY EXPECTATIONs
Benefits of Hiring Remote Talent in LATAM
Real-Time Collaboration
Machine learning engineers for hire in LATAM offer a major advantage: time zone alignment with the U.S. Engineers in countries like Colombia, Mexico, or Argentina typically work within 1–3 hours of U.S. time zones, enabling real-time collaboration. This proximity boosts productivity—especially since voice and video calls decrease by 11% for every hour of time difference between team members.
Hire at a lower cost
Hiring engineers in LATAM is significantly more affordable than in the U.S., with monthly rates typically ranging from $3,750 to $6,250. This cost advantage allows companies to access highly skilled talent while optimizing budgets and extending runway-without compromising expertise.
Cultural Compatibility
Engineers in LATAM tend to have strong cultural alignment with U.S. teams - similar work values, communication styles, and collaborative mindsets. Most are fluent in English, familiar with agile methodologies, and bring experience working with international clients. Cultural fit makes integration seamless, reducing onboarding time and enabling teams to work as one from day one.
Cost of a Machine Learning Engineers
Teilur Talent is disrupting the international recruiting industry through transparent pricing.
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Access to top machine learning engineers for hire
A machine learning engineer is like the secret weapon behind intelligent, automated systems. They are the ones who take messy data and turn it into actionable information using algorithms, models, and code. But they don't stop there. Unlike data scientists who focus on analytics, ML engineers build and deploy machine learning models in real-world applications that scale. This means they help your product or platform learn from data and improve over time: think recommender systems, fraud detection, predictive analytics, and more.
These professionals work with technologies like Python, TensorFlow, PyTorch, Scikit-learn, AWS, and Docker, and often collaborate with data teams, software engineers, and product managers. What's the benefit? Speed and efficiency. They automate repetitive processes like customer segmentation, forecasting, or content filtering, saving teams hours of manual work. Whether you're launching a financial technology product, an AI-powered chatbot, or a logistics optimization tool, machine learning engineers bring scalability and intelligence to your technology stack, and that's a huge competitive advantage.
An end-to-end recruiting solution
Recruiting:
We carefully match you to top engineers based on your business needs, mission, company size, and industry.
Payroll:
We simplify international payroll, you can pay monthly via ACH, Ethereum, and we accept any credit card for your convenience.
Contract & Compliance:
Forget about headaches of legal regulation in other regions, we take care of the contract, compliance, and legal matters.
Benefits:
We believe a happy talent is the key to success. We take care and assign the benefits for the engineer you have choosen with us.
A simple process to start
We match you with the right talent depending on your business model
Client Reviews
Got questions? We've got answers.
The cost of hiring a Machine Learning Engineer can vary depending on their level of experience, area of specialization, and location. In Latin America, companies can typically expect to pay between $3,750 and $6,250 per month for a qualified engineer. This range covers mid-level to senior professionals who are capable of independently handling complex ML tasks and integrating models into production systems.
There are several effective ways to find machine learning engineers for hire, including exploring remote talent platforms, browsing freelance networks, or using professional communities. You can also connect with regional tech recruiters in areas with strong engineering talent, such as Latin America, to access pre-vetted candidates with AI and data science expertise.
Several Latin American countries are recognized for producing excellent ML engineers, with Brazil, Argentina, Colombia, and Mexico often standing out. These countries benefit from robust university systems, active tech hubs, and growing ecosystems that support AI research and startups. Argentina and Colombia, for instance, have a particularly high number of bilingual professionals and offer favorable time zone alignment with North America.
Machine learning engineers for hire, start by outlining your project goals and required skills, such as NLP, computer vision, or model deployment. Then, evaluate candidates based on coding ability, experience with ML frameworks like TensorFlow or PyTorch, and real-world project work. Reviewing GitHub profiles or portfolios can help verify hands-on expertise.
Machine learning is commonly divided into four types: supervised, unsupervised, semi-supervised, and reinforcement learning. Supervised learning uses labeled data for tasks like classification and regression, while unsupervised learning finds patterns in unlabeled data, such as clustering. Semi-supervised learning blends both approaches when labeled data is limited. Reinforcement learning trains models through feedback from actions, often used in robotics and game AI.