11 Top Countries for Offshoring Your Machine Learning in 2025

Machine learning (ML) is transforming industries, and companies now rely on it to stay competitive. But hiring ML experts locally can be challenging due to higher salaries fueled by high living costs, talent shortages, and intense competition from major tech firms also seeking qualified candidates from within the same limited talent pool.

Many businesses are finding that offshoring ML development offers an effective balance of cost management and quality outcomes. By partnering with talented professionals in other countries, companies can access specialized expertise that may be hard to find locally while staying on budget. 

Wondering which regions make the most sense for offshoring your machine learning projects? Let's take a look at the leading destinations that offer excellent options for your ML development needs.

11 Top Countries for Offshore Machine Learning

Hiring an offshore ML engineer gives you access to outstanding talent at more competitive rates. When you select the right location, you benefit from the specialized skills of experienced developers, robust tech ecosystems, and cost-effective pricing structures.

Here are 11 leading countries for offshoring machine learning development, each offering distinct advantages for your projects. 

1. Brazil

With a growing number of businesses investing in ML capabilities, the demand for skilled IT engineers continues to increase. Brazil's machine learning market is projected to reach $23.13 billion by 2030, establishing it as a hub for AI-driven innovations. 

Several leading educational institutions, such as the University of São Paulo and the State University of Campinas, produce high-caliber IT graduates who are prepared to tackle global projects. Brazil's AI and data science communities are also experiencing substantial growth, fostering an environment where both businesses and professionals can benefit from cross-border collaboration.

2. India

India boasts the world's largest pool of STEM graduates, creating a massive talent pipeline that fuels a dynamic IT sector. This abundant supply of professionals helps keep labor costs competitive while ensuring businesses have access to a vast pool of talent.

Indian technology firms have been quick to embrace AI and ML solutions. This technical expertise, paired with cost advantages, makes India a long-trusted and attractive destination for offshoring various tech projects.

3. Mexico

Mexico has solidified its reputation as a major tech center, with cities like Guadalajara (often referred to as the Silicon Valley of Mexico) and Monterrey (a hub for Cisco, HP, Intel, and Oracle, among many other corporations) leading the charge. 

Many Mexican AI/ML engineers and developers bring valuable experience working directly with US-based companies, thanks to the two countries’ long standing trade relationship and geographical proximity. Time zone compatibility facilitates smooth collaboration between teams. 

4. Argentina

Buenos Aires and La Plata have some of Latin America’s best universities for AI research. Many of the region's top outsourcing firms, like BairesDev and Globant, were also founded there, giving local IT engineers and specialists exposure to international projects early in their careers.

That pro-IT environment means businesses offshoring to Argentina can find experienced ML professionals who understand global development standards while also contributing to the advancement of AI within the country. 

5. Poland

Poland is a rising European tech powerhouse, with over 60,000 technology companies and 10 unicorn startups, reflecting its robust, thriving tech ecosystem.

The country's strong educational system consistently produces highly skilled AI/ML specialists. Polish IT professionals have earned a reputation for their technical precision and ability to handle complex AI-driven projects, making them valuable partners for  organizations looking for dependable engineering talent.

6. Colombia

Colombia's tech sector has experienced remarkable growth, with Medellín emerging as a hotspot for AI/ML and software development. The World Economic Forum partnered with the city to establish the Centre for the Fourth Industrial Revolution (C4IR), which focuses on advancing AI and accelerating the adoption of various technologies.

The Colombian government has also demonstrated a clear commitment to AI advancement through a new public policy initiative dedicated to promoting it, allocating around $120 million through 2030. This program aims to strengthen research capabilities, encourage ethical AI implementation, and position Colombia as a regional leader in technology.

7. Ukraine

Despite the ongoing geopolitical struggles, Ukraine's tech industry, with its strong education system and highly skilled workforce, has demonstrated impressive resilience and adaptability.

The country ranks second in Central and Eastern Europe for AI-focused companies. Businesses offshoring their tech development to Ukraine can tap into an already established network of experienced engineers, researchers, and developers.

8. Vietnam

Vietnam is positioning itself as a global AI hub, with government-backed digital transformation initiatives and increasing foreign investment from major players like Amazon, Samsung, NVIDIA, and Google.

These investments have fueled AI research and development, leading to Vietnam's rise in its AI readiness ranking within Southeast Asia. With the country’s strong emphasis on innovation and cost-effective AI development, businesses that offshore machine learning projects to Vietnam benefit from the talent of skilled professionals who are at the forefront of technological advancement.

9. The Philippines

The Philippines boasts a large English-speaking workforce with an expanding number of AI/ML specialists. In 2025, the country's IT services sector is projected to reach $2.5 billion in revenue—a growth nurtured by substantial investments in AI automation and data analytics.

Filipino expertise is particularly notable in practical applications like AI-driven customer support, fraud detection, and chatbot development, making it a great destination for offshoring applied AI solutions. 

10. China

China's AI talent pool represents one-tenth of the world’s most elite AI researchers, reflecting the country's dedication to technological innovation and the adoption of new technologies.

With leading universities and tech companies in China driving advancements in AI/ML and automation, businesses offshoring IT development to the country gain access to talented professionals who are helping to shape the future of AI.

11. Chile

The Latin American Artificial Intelligence Index 2024 identifies Chile as the leader in AI development in the region (ILIA 2024). The country has taken AI adoption very seriously, launching its National Artificial Intelligence Policy in 2021 and updating it in 2024 to keep pace with new technology.

Chile is also home to one of the region's largest data center markets, with a National Data Center Plan that aims to bring in $2.5 billion in investments. Offshoring ML engineering projects to Chile means working with experts in a country that has made AI development and infrastructure a clear priority. 

Why Offshore Machine Learning in Latin America Stands Out

Hiring a nearshore ML engineer means offshoring development to a professional in a nearby country or region, like Latin America (LatAm) for US businesses. 

While cost advantages come naturally due to lower living expenses (as with other offshoring locations), LatAm offers substantially more benefits than just savings.

Here’s why LatAm stands our for nearshoring ML talent:

• Time zone alignment: Working with ML engineers in similar time zones allows for real-time communication and seamless collaboration. This is especially advantageous in industries like finance and healthcare, where timely decision-making is key. Rather than coping with delayed communication cycles due to significant time zone differences, teams can resolve issues and push projects forward during overlapping working hours.
• Cultural compatibility: Many LatAm professionals are familiar with US business standards, making collaboration and compliance smoother. Cultural alignment and shared work expectations lead to fewer miscommunications and greater team integration.
• Bilingual talent: Many ML engineers in the region are fluent in both English and Spanish. This English language proficiency minimizes communication barriers and proves especially valuable for companies serving diverse customer populations or developing multilingual AI applications.
• Strong tech ecosystem: The LatAm region has rapidly developed its AI and software industries, with professionals becoming well versed in cutting-edge technologies and best practices.

Beyond choosing the right offshoring location for your business needs, it's also important to look for key skills when hiring an ML engineer, including the right mix of technical expertise and soft skills.

While hiring independently offers complete control over your ML projects, it can strain businesses with limited resources and time. Staffing agencies can help you find qualified tech professionals without the lengthy recruitment and hiring processes. 

These agencies have access to pre-vetted talent, which cuts down on the time spent on screening candidates and accelerates the onboarding process.

For deeper insights into the hiring process, read our article on how to hire a remote ML engineer. 

Final Thoughts

The offshoring destination you choose can have a big impact on your ML projects. And for US companies looking for a combination of quality, cost-efficiency, and real-time collaboration, nearshoring to LatAm stands out as the best option.

Curious to learn more about nearshore hiring? Read our article on why hundreds of leading US companies are hiring LatAm talent.

You can also explore our salary guide to compare the cost advantages of hiring in Latin America versus the US.