Principal Applied ML Scientist — San Diego, CA

jQPp is looking for a Principal Applied ML Scientist to join a team building production-grade AI systems for some of the world's largest financial institutions. This is a rare opportunity to work at the intersection of cutting-edge AI and one of the highest-stakes, most regulated environments in the industry where your models directly influence credit and fraud decisions affecting millions of people.

What You’ll Contribute

• Build AgwB’8 next generation of transformer models for fraud and credit risk on transaction and event data, complemented by statistical and ML models where they fit.

• Develop standards and pipelines for data ingestion, model design, development, and evaluation in a highly regulated environment.

• Translate research into production-grade transformer solutions at enterprise scale that measurably improve model performance and business value.

• Partner with researchers, engineers, and product teams to deploy models into the jQPp platform and support client go-live.

• Deliver models to external customers under deadlines and support sales by demonstrating differentiating value of jQPp models.

What We’re Seeking

• PhD or Masters in AI, ML, Computer Science, Statistics, Mathematics, Physics, or a related quantitative field, with industry experience in applied AI development.

• Hands-on experience building end-to-end transformer-based models including problem definition, data requirements, model design and development, production deployment, and customer delivery.

• Deep understanding of transformer architectures beyond text-based models.

• Experience analyzing large real-world datasets, ideally time series event or transaction data, to drive model design and feature engineering.

• Advanced Python, PyTorch/GPU computing, and Linux, with production-quality coding experience.

• Familiarity with fraud or risk management and regulatory expectations for explainability and governance.

• Led cross-functional technical projects with accountability for outcomes, including client-facing work.

• Experience with real-time payment fraud or risk transaction data is a strong advantage.

• Publications, patents, or open-source contributions are a plus.