AI and ML Engineer Jobs in Argentina: Opportunities, Skills, and How to Land One

Growing demand and where the jobs are

Argentina has seen a sustained increase in AI and ML hiring over the past few years. Buenos Aires remains the primary hub, hosting large tech companies, AI startups and research labs, but significant activity is also happening in Córdoba, Mendoza and Rosario. Local startups focus on fintech, healthtech and agritech, while multinationals and service companies hire for applied ML, data engineering and MLOps roles. Remote-first companies broaden opportunities further — many Argentine engineers work for U.S. and European firms while living locally, attracted by competitive pay in dollars and flexible schedules. Job growth is driven by businesses deploying recommendation systems, computer vision for industrial automation, NLP for customer support, and predictive analytics for finance and agriculture.

Skills, qualifications, and what employers look for

Employers typically look for a mix of theoretical ML knowledge and practical engineering skills. Core requirements often include: knowledge of machine learning algorithms (supervised, unsupervised, deep learning), proficiency in Python and libraries like TensorFlow, PyTorch, scikit-learn, data manipulation with pandas, and experience with SQL. For production roles, companies value MLOps skills (Docker, Kubernetes, CI/CD), cloud experience (AWS, GCP, Azure), model deployment and monitoring, and data pipeline engineering. Strong candidates showcase real projects (GitHub, Kaggle, personal portfolio), solid math foundations (linear algebra, probability), and domain experience relevant to the employer (e.g., NLP for chatbots, CV for manufacturing). Soft skills — collaboration, clear communication in Spanish and English, and product-focused thinking — often tip the scales during hiring.

Finding roles, salary expectations and career growth

To find AI/ML roles in Argentina, use a combined approach: monitor local job boards (Bumeran, ZonaJobs), LinkedIn, specialized tech platforms (Stack Overflow Jobs, GitHub Jobs), and global remote marketplaces (Remote OK, WeWorkRemotely). Attend meetups and conferences in Buenos Aires, join local Slack/Telegram communities, and network with university research groups. Salaries vary by experience, employer and contract currency — junior ML engineers may earn modest local salaries, while senior engineers at multinational firms or remote roles paid in USD can earn substantially more. Expect significant variation: entry-level roles might be in the lower-to-mid local market range, while experienced engineers with MLOps or leadership skills command top-tier compensation. Career progression often moves from data scientist/ML engineer to senior engineer, team lead, or ML architect — plus opportunities to transition into product or research tracks if you prefer innovation-driven roles.