Experienced Remote Talent for AI and Deep Tech
ML engineers, data engineers, AI product managers, and technical specialists from Latin America — placed in 21 days at 45 to 59 percent below US market rates.
Hiring Challenges in AI and Deep Tech
ML and AI expertise in the US is extraordinarily expensive. Engineers with 3 to 5 years of ML experience command $150,000 to $250,000. The equivalent from Brazil or Argentina with production ML experience, strong Python and PyTorch skills, and US timezone alignment costs $65,000 to $95,000 — a saving of 45 to 59 percent that directly extends your runway.
Competition from big tech and well-funded AI startups makes hiring nearly impossible. Google, OpenAI, and Anthropic are competing for the same US engineers you are — and winning on comp. LATAM top technical talent is world-class and not yet priced out of reach for early-stage AI companies.
Every month of hiring delay is a month your competitor is shipping. Long hiring cycles delay model development, product launches, and time to market. Our LATAM AI and engineering searches deliver first shortlists in 5 to 7 days, with most clients making a hire by day 21.
Building an AI company requires more than just engineers. Sales, operations, and product functions all need to scale alongside your technical team. LATAM has deep talent pools for BDR, product managers, and data analysts — all critical for taking AI products to market.
Roles We Place in AI and Deep Tech
Technical
Product and Go-to-Market
Why LATAM Talent Works for AI and Deep Tech
Brazil dominates engineering placements — representing the highest concentration of IT and engineering talent in LATAM. Argentina is number two. Together they produce world-class ML engineers, data engineers, and AI specialists from top technical universities with strong mathematics, statistics, and computer science foundations.
Production-ready technical skills from day one. LATAM AI engineers are fluent in Python, TensorFlow, PyTorch, Spark, and modern cloud platforms. Many have contributed to production ML systems at global tech companies and US-based AI startups. Demand for LATAM software and AI engineers grew 250 percent year over year — the market has validated the quality.
Cost savings that extend your runway by months. A machine learning engineer costs $75,000 to $95,000 in LATAM versus $180,000 to $250,000 in the US. A data engineer costs $69,000 versus $126,000 — a 45 percent saving. For an early-stage AI company, a team of three LATAM engineers costs what one US-based ML engineer costs — that difference is 6 to 12 months of additional runway.
66 percent longer retention than US hires. AI engineering talent in the US churns constantly — poached by better-funded competitors. LATAM engineers stay 66 percent longer on average. More continuity on your model development. More institutional knowledge. Less time rehiring and retraining.
Related Industries
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