### About Plata Plata is one of the fastest-growing fintech companies in the world. In just 3 years, we've grown to 3M+ customers and reached a $5B+ valuation. We're now strengthening our Risk & Decisioning core team and are looking for a Principal AI Engineer to set the technical bar and build best-in-class, production-grade models that materially move business metrics. ### Why this role - You will own our foundation model program end to end - from research direction to models running in production and driving real credit decisions. - Your models directly move the numbers that matter: cost of risk, approval rates, and portfolio NPV across a fast-scaling credit portfolio. - You'll work with one of the richest financial datasets in LATAM billions of transactions and behavioral events across 3M+ customers, growing daily. ### What you'll do - Build an end-to-end **foundation model** over financial event sequences - transactions, credit bureau data, and in-app behavioral events with subsequent fine-tuning for downstream business tasks: underwriting (PD), credit limit strategy, fraud detection, collections, and propensity models. - Drive technical decisions end-to-end: methodology → implementation → performance and latency → robustness, interpretability, and regulatory compliance. - Take models from research to production: training infrastructure, evaluation frameworks, model serving, latency/cost optimization, and monitoring. - Research state-of-the-art approaches in the industry, publish your own work, and speak at leading conferences. - Mentor senior engineers and scientists; own technical standards for model development across the team (design reviews, evaluation methodology, deployment practices). - Communicate results clearly to cross-functional stakeholders: product, risk, business, and leadership. ### What makes you a great fit - Proven experience applying deep learning to **sequential data** - transformer architectures on event/transaction sequences strongly preferred, but not required. - Strong foundation in mathematical statistics and probability theory. - Deep understanding of machine learning algorithms (GBM, MLP, CNN, RNN, Transformers, etc.) - Experience taking large models to production: distributed training, model serving, latency/cost trade-offs. - Ability to strike a reasonable balance between solution complexity and practical applicability. - Strong mathematical or technical education - degree in mathematics, physics, or CS from a top technical university - Kaggle Competitions Master/Grandmaster or equivalent (a plus); experience developing models in banking or consumer lending (a plus) - Strong communication skills. ### Our ways of working - **Innovative Spirit:** a commitment to creativity and groundbreaking solutions - **Honest Feedback:** valuing open, transparent communication - **Supportive Team:** a strong, collaborative community - **Celebrating Achievements:** recognizing our wins together - **High-Tech Environment:** a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances ### Our benefits - Relocation support to one of our hubs - Mexico, Cyprus, Serbia, Spain with assistance for the employee and their family - Flexible work from one of our offices or remote - Healthcare coverage - Education budget: language lessons, professional training and certifications - Wellness budget: mental health and fitness activity reimbursements - Vacation policy: 20 days of annual leave and paid sick leave