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Accountabilities:
- Identify high-value opportunities for foundation model research and drive execution against the research roadmap.
- Develop next-generation fraud detection solutions using deep learning and representation learning on large-scale sequential data.
- Take models through the complete ML lifecycle including deployment, monitoring, and production optimization.
Requirements:
- 4+ years of experience in applied machine learning or quantitative modeling with hands-on foundation model work.
- Strong Python and SQL skills with ability to process very large datasets.
- Experience in fraud, AML, or adversarial machine learning is a strong asset.
Benefits:
- Generous compensation package combining cash and equity.
- Remote-first culture with flexible paid time off and year-end break.
- Comprehensive health, dental, vision insurance and RRSP matching for eligible employees.
Partner Company
The company is a fintech organization focused on fraud detection and financial risk using AI and deep learning. It operates with a remote-first culture and a collaborative, autonomous team.