Let’s get one thing straight: San Francisco will be the top AI hub for the next decade. It has four times the activity of any other AI city hub. A quarter of the US’s AI conference papers, patents, and companies are there.
But San Francisco is exorbitantly priced for most business owners. AI is growing, but we need a pool of skilled yet affordable talent to keep it on its growth trajectory. We are also living in a time that prioritizes the inclusion of women and people of color in the AI industry. Finding a diverse and skilled pool of professionals takes a lot of work, even in tech-heavy regions.
This talent gap has led many companies to consider AI outsourcing. This article will guide you in selecting the best location for your offshore ML team. We’ll consider cost, talent availability, infrastructure, and language compatibility factors.
What Makes an AI Talent Hub?
An AI talent hub is a region with a high concentration of AI and ML professionals. These hubs often have the right academic institutions, tech companies, and government support, creating an ideal environment for AI development. Availability of skilled workers, cost, infrastructure, and time zone compatibility are essential factors to consider when choosing a hub for your offshore ML team.
The goal is to find a balance between talent quality and cost-effectiveness. Some regions offer lower costs but might have a different experience level than others. Matching the hub’s strengths with your company’s specific needs is essential.
Critical Factors for Choosing a Location to Hire an ML Engineer
Talent Availability
Some regions are known for having a pool of AI talent. In contrast, others might be less developed in this area—research local universities, tech communities, and industries contributing to the talent pool. Consider how quickly you can fill roles and whether a steady stream of new graduates is entering the field.
For example, countries like India and China produce thousands of tech graduates yearly. While both nations are known for their technical expertise, they differ in cost, business culture, and infrastructure.
Cost
The cost of hiring, living, and office space varies widely between regions. Eastern European countries like Poland and Ukraine offer skilled ML professionals at a lower price than NY or London. Southeast Asian countries, like the Philippines and Vietnam, also present affordable hiring options.
Infrastructure and Time Zones
An excellent offshore location needs reliable infrastructure, internet connectivity, transportation, and office spaces. Additionally, consider the time zone differences. Locations closer to your time zone, such as Latin America for U.S.-based companies, allow for more accessible communication. However, some businesses prefer working with regions further away, where teams can work on projects while the home office is offline–creating a 24/7 availability of services.
Language Compatibility
English is the primary language for many global tech hubs, but proficiency levels differ. Countries with high English proficiency, such as India, the Philippines, and several Eastern European nations, might better fit companies requiring fluent communication.
Top AI Talent Hubs for Offshore ML Teams
India
India is one of the largest sources of tech talent in the world. With solid engineering and IT education systems, the country produces thousands of AI and ML professionals each year. Bangalore, Hyderabad, and Pune have become tech hubs, attracting large global companies.
Pros:
- The immense talent pool of skilled AI and ML professionals
- Strong English proficiency
- Affordable labor costs
- Reasonably priced office spaces and equipment
- Excellent offshoring guides and partners are available
- Can create a 24/7 work cycle easily
Cons:
- Infrastructure can be uneven depending on the city
India will always be a top choice for companies building a cost-effective offshore ML team while ensuring access to well-educated professionals.
Eastern Europe: Poland and Ukraine
Eastern Europe is also a hub for tech talent, particularly in AI and machine learning. Poland and Ukraine are known for their highly educated workforces and excellent technical skills.
Pros:
- Skilled ML talent at lower costs compared to Western Europe
- Proximity to European markets
- Excellent English proficiency
- Solid professionalism and ability to do focused work
- Strong infrastructure for sustained growth
Cons:
- Slightly higher costs compared to other offshore regions
- Geopolitical factors, especially in Ukraine, can be a concern
Eastern European countries are great options for companies that want to stay close to Europe while cutting costs. Many businesses have successfully set up offshore ML teams in cities like Warsaw, Kraków, and Kyiv.
China
China is a global leader in AI, driven by government initiatives and a booming tech sector. Beijing and Shenzhen are among the key hubs for AI talent.
Pros:
- Strong government support for AI development
- Large and growing talent pool
- An increasing number of AI-focused research institutions and startups
- Most tech professionals speak fluent English
- The infrastructure supports the growth of AI hubs
Cons:
- Language barriers, such as English proficiency, still exist, although it’s improving fast
- Complex business regulations for foreign companies.
China offers outstanding talent availability, but companies must weigh the cultural, regulatory, and language challenges before setting up an offshore team there.
Latin America: Brazil, Mexico, and Argentina
Latin America has become an increasingly attractive destination for U.S. companies looking to outsource or build offshore teams. São Paulo, Mexico City, and Buenos Aires have seen a growing tech sector.
Pros:
- Close timezone alignment with the U.S.
- Lower labor costs and affordable working spaces
- A growing pool of proficient tech talent
- Friendly work environment all over the region, driving creativity and innovation
Cons:
- Smaller talent pool compared to Asia or Eastern Europe
- Slightly higher cost compared to India and the Philippines
For companies in the U.S., Latin America offers the advantage of proximity and similar time zones, making collaboration easier. However, the talent pool might be more limited compared to other regions.
Southeast Asia: Philippines and Vietnam
Southeast Asia has seen significant growth in its tech sector over the past decade. The Philippines and Vietnam, in particular, have become known for their offshore talent, especially in IT and software development.
Pros:
- Lower labor costs and affordable working spaces
- Strong English proficiency in the Philippines.
- The rapidly growing tech sector
- Disciplined and focused working environment; excellent work culture
Cons:
- Smaller talent pool compared to India or Eastern Europe.
Southeast Asia is attractive for companies looking for affordable offshore solutions with good communication and is set to improve. Manila and Ho Chi Minh City are key tech hubs in the region.
Long-Term Considerations
Scaling Your Team
Some regions offer an abundant talent pool for initial hires but might need help to meet demand as your team expands. Look for hubs with a steady pipeline of tech graduates and experienced professionals. India, for example, has a large talent base that allows for rapid scaling. Eastern Europe also has a strong talent pipeline, especially in Warsaw and Kyiv.
Retention and Talent Development
Once you have set up your offshore team, you must consider retaining them and ensuring their growth. Offering competitive salaries and career development opportunities helps. Regions with solid local ecosystems, such as India and China, often provide access to additional training and development resources. Invest in ongoing education so your offshore team can stay up-to-date with AI trends and technologies. AI is evolving, and this will help everyone involved.
Conclusion
The best location for you depends on your company’s specific needs.
As mentioned earlier, SF is the AI place to be now. But this is also a narrow and non-inclusive approach. The objective of a fourth Industrial Revolution isn’t to have amazing tech hubs in pockets of prosperity but to use tech to create prosperity everywhere. Not every owner can afford to build an AI team in the Bay Area, and there are excellent ML engineers in every tech hub. By carefully evaluating each hub’s strengths, you can build a highly skilled and cost-effective offshore ML team that drives your business forward.
The objective is to have SF-level hubs in every city, which is very achievable now.
