Artificial intelligence is the engine behind today’s most innovative products, from ChatGPT-style assistants and self-driving cars to personalized healthcare and fraud detection.
As companies rush to integrate AI into their operations, the demand for skilled AI engineers has skyrocketed. But one question is on every founder’s, CTO’s, and hiring manager’s mind: how much does it cost to hire an AI engineer?
The short answer: it depends. Salaries for AI engineers vary widely based on experience, specialization, and location.
A senior AI engineer in Silicon Valley may command a six-figure salary north of $200,000 per year, while equally talented professionals in Latin America or Eastern Europe can deliver the same results at a fraction of the cost. Understanding these differences is crucial for businesses looking to balance innovation with budget.
In this guide, we’ll break down the average AI engineer salary ranges, explore the factors that influence costs, compare hiring models (in-house, freelance, agency, nearshore), and show you how companies are building top-tier AI teams without overspending.
What Does an AI Engineer Do?
Before diving into salaries and hiring costs, it’s important to understand what an AI engineer actually does.
While the title may sound similar to machine learning engineer or data scientist, an AI engineer typically plays a broader, more applied role. They’re the professionals who take cutting-edge AI models and turn them into real-world solutions that drive business value.
Core responsibilities of an AI engineer include:
- Designing and developing AI models using frameworks like TensorFlow, PyTorch, and Keras.
- Training and fine-tuning algorithms for tasks such as natural language processing (NLP), computer vision, recommendation systems, or predictive analytics.
- Integrating AI into existing products and workflows, ensuring that models don’t just work in theory but deliver results at scale.
- Optimizing performance and scalability, from managing large datasets to deploying AI in cloud environments with GPUs and distributed computing.
- Collaborating with cross-functional teams, including data scientists, product managers, and software engineers, to align AI capabilities with business goals.
In other words, AI engineers bridge the gap between research and implementation. They take the breakthroughs happening in academic and experimental AI and make them practical for companies to use in customer-facing applications, internal tools, or automation initiatives.
Because of this, their work requires not just technical expertise but also problem-solving, creativity, and an understanding of how AI impacts business strategy. This unique mix of skills is what makes AI engineers so valuable and why the cost of hiring them is often higher than for other technical roles.
Factors That Affect AI Engineer Salaries
The cost of hiring an AI engineer isn’t one-size-fits-all. Multiple factors come into play when determining how much you’ll need to budget for this role. Understanding these variables helps you plan smarter and avoid overpaying while still attracting top talent.
Experience Level
Just like in any technical field, experience makes a major difference.
- Junior AI engineers with 1–2 years of experience typically support model training and testing.
- Mid-level engineers often take ownership of projects, handling everything from data preprocessing to deploying models.
- Senior AI engineers or leads not only design advanced architectures but also guide strategy, mentor teams, and ensure AI initiatives align with company goals.
Specialization
AI is a broad field, and costs shift depending on the expertise you need. Engineers specializing in natural language processing (NLP), computer vision, or generative AI often command higher salaries due to demand and the complexity of their work.
Location
Geography plays one of the biggest roles in salary differences.
- Hiring in the U.S. (especially Silicon Valley, New York, and Boston) comes with the highest price tag.
- Europe and Canada offer slightly lower salaries, though still competitive.
- Nearshore regions like Latin America provide highly skilled engineers with time-zone alignment at significantly reduced costs; often 50–70% less than U.S. rates.
Industry
An AI engineer working in finance, healthcare, or cybersecurity (industries where AI can drive massive ROI) may earn more than one working in smaller-scale retail or education startups.
Company Size
Startups and mid-sized companies may not always match the salaries offered by big tech firms, but they often compete by offering equity, growth opportunities, or flexible work setups.
Average Salary Ranges (U.S. vs. Global)
So, how much does it really cost to hire an AI engineer? Salaries vary widely depending on region and seniority, but here are the averages you should expect:
United States (Highest Cost Market)
- Junior AI Engineer: $90,000 – $120,000 per year
- Mid-Level AI Engineer: $130,000 – $170,000 per year
- Senior AI Engineer / Lead: $180,000 – $250,000+ per year
Europe & Canada (Moderate Cost Market)
- Junior AI Engineer: $70,000 – $100,000 per year
- Mid-Level AI Engineer: $110,000 – $140,000 per year
- Senior AI Engineer / Lead: $150,000 – $200,000 per year
Latin America (Cost-Effective Nearshore Option)
- Junior AI Engineer: $25,000 – $40,000 per year
- Mid-Level AI Engineer: $45,000 – $70,000 per year
- Senior AI Engineer / Lead: $75,000 – $110,000 per year
Asia (Wide Range Based on Country)
- Junior AI Engineer: $20,000 – $35,000 per year
- Mid-Level AI Engineer: $40,000 – $60,000 per year
- Senior AI Engineer / Lead: $65,000 – $100,000 per year
As you can see, hiring in the U.S. can cost 2–3 times more than hiring equally qualified AI engineers in Latin America, where time-zone alignment makes collaboration seamless for U.S. teams. This is why many startups and enterprises are nearshoring their AI teams.
Additional Hiring Costs to Consider
While salaries make up the bulk of your expenses, they’re not the full picture. Hiring an AI engineer, whether locally or remotely, comes with a set of additional costs that can significantly impact your budget. Overlooking these can lead to surprises down the road.
Recruitment and Hiring Fees
Finding qualified AI engineers is tough, and recruiters or specialized platforms often charge high fees. Traditional agencies can take 20–30% of a candidate’s first-year salary.
Onboarding and Training
Even the most skilled AI engineer will need time to adapt to your company’s data infrastructure, workflows, and tools. Expect to invest in onboarding programs, documentation, and sometimes formal training.
Benefits and Perks
In the U.S., benefits such as health insurance, retirement contributions, and stock options can add 20–30% on top of base salary. Even remote hires often expect perks like home office stipends, professional development, or wellness benefits.
Infrastructure and Tools
AI engineers rely on powerful infrastructure: cloud computing credits, GPUs, collaboration platforms, and enterprise-level licenses for tools like TensorFlow, PyTorch, or Hugging Face APIs. These costs scale quickly depending on your AI project.
Opportunity Costs of Delays
Perhaps the most overlooked expense: the cost of waiting. If your AI hire takes months to secure, you risk losing competitive advantage, slowing product development, or missing customer demand windows.
When calculating the cost of hiring an AI engineer, add at least 20–40% to the base salary for these hidden expenses.
Companies that nearshore to Latin America often save not just on salaries but also on recruiting time, reducing many of these overheads. If you’d like to learn more about this approach, schedule a free call with us today!
Hiring Models and Their Costs
When deciding how to bring an AI engineer onto your team, it’s not just about who you hire, but how you hire. Different hiring models come with different costs, timelines, and levels of flexibility. Here’s how they stack up:
In-House (Full-Time Hire)
- Cost: Highest (salary + benefits + overhead).
- Pros: Long-term commitment, deep integration into your team, strong company loyalty.
- Cons: Lengthy and expensive recruitment process, limited flexibility if needs change.
- Best for: Companies building a core AI team as a strategic asset.
Freelancers / Contractors
- Cost: Hourly/project rates ($50–$200+/hr depending on skill and region).
- Pros: Flexible, no long-term commitments, great for short-term projects or prototypes.
- Cons: Limited availability, variable quality, less accountability, and risk of delays.
- Best for: Startups testing ideas or companies with one-off AI tasks.
Agencies / Consultancies
- Cost: Premium pricing (often higher than in-house, with project retainers of $30k+).
- Pros: Immediate access to specialized expertise, fast turnaround, proven processes.
- Cons: Very expensive, knowledge often stays with the agency, less control over individual engineers.
- Best for: Enterprises needing speed over cost-efficiency.
Nearshore Talent (Latin America)
- Cost: 50–70% less than U.S. salaries, with fewer overhead costs.
- Pros: Full-time dedicated engineers, cultural and time-zone alignment, high skill levels, cost-effective flat-fee hiring through agencies like South.
- Cons: Requires a reliable vetting and onboarding partner.
- Best for: U.S. companies that need strong AI talent at scale without Silicon Valley price tags.
The Takeaway
Hiring an AI engineer is one of the most impactful investments a company can make today. From automating workflows to powering cutting-edge products, these professionals bring the expertise that turns raw data into real business results.
But with salaries soaring in the U.S. and Europe, many companies struggle to balance innovation with cost.
The good news? You don’t have to choose between quality and affordability. By nearshoring to Latin America, you gain access to highly skilled AI engineers who work in your time zone, integrate seamlessly with your team, and deliver at a fraction of the cost.
Whether you’re a startup looking to hire your first AI engineer or an enterprise scaling a full AI team, nearshore hiring gives you the flexibility, speed, and savings you need to stay ahead.
Ready to hire top AI engineers without Silicon Valley price tags?
Partner with South to build your AI team in Latin America. We connect U.S. companies with vetted, highly skilled talent at transparent flat fees, so you can focus on scaling your business, not overpaying for hires.
Schedule your free call with our team now!
Frequently Asked Questions (FAQs)
How much does it cost to hire an AI engineer in the U.S.?
In the U.S., AI engineer salaries typically range from $90,000 to over $250,000 per year, depending on experience, specialization, and location. Senior engineers in Silicon Valley often command the highest salaries.
Are AI engineers more expensive than data scientists?
Yes, in many cases. While data scientists focus on analyzing and interpreting data, AI engineers are responsible for building, deploying, and scaling AI systems. This added layer of implementation and engineering often results in higher salaries.
Is it cheaper to hire AI engineers in Latin America?
Absolutely. AI engineers in Latin America earn between $25,000 and $110,000 per year, which is 50–70% less than U.S. salaries. With time-zone alignment and strong technical skills, nearshore engineers offer excellent value for U.S. companies.
What skills should I look for when hiring an AI engineer?
Key skills include Python, TensorFlow, PyTorch, NLP, computer vision, data modeling, cloud platforms (AWS, GCP, Azure), and experience deploying AI models into production. Soft skills like problem-solving, adaptability, and collaboration are equally important.
What’s the best hiring model for AI engineers?
It depends on your needs:
- In-house hires are best for long-term, strategic roles.
- Freelancers work well for short-term or experimental projects.
- Agencies deliver speed but come with high costs.
- Nearshoring to Latin America offers the best mix of affordability, skill, and team integration for U.S. companies.
How quickly can I hire an AI engineer through nearshoring?
With a partner like South, many companies can hire a pre-vetted AI engineer in as little as 2–4 weeks, compared to the months it often takes to recruit locally in the U.S.
