Applied AI/ML Engineer

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.

Preferred qualifications:

• Experience working in a financial, audit, or highly regulated domain where deterministic accuracy and auditability are paramount.
• Experience in full-stack development for end-to-end machine learning solutions.
• Experience building Agentic tools and systems (production-ready, not POCs).
• Experience in classical ML modeling (e.g., time-series forecasting, tree-based models) alongside modern Large Language Model (LLM)/Generative AI tooling.
• Expertise in developing and deploying AI/ML models and utilizing modern observability/monitoring tools to track performance, latency, and model drift.
  • Excellent communication and storytelling skills, with a proven ability to translate complex technical architectures and probabilistic model behaviors to executive finance leadership.