Applied AI/ML Engineer

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

Preferred qualifications:

• 8 years of experience in full-stack development for end-to-end machine learning solutions.
• Experience building Agentic tools and systems (production-ready, not POCs).
• Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.
• Experience in classical ML modeling (e.g., time-series forecasting, tree-based models) alongside modern Large Language Model (LLM)/Generative AI tooling.
• Demonstrated expertise in developing and deploying AI or ML models and utilizing modern observability/monitoring tools to track performance, latency, and model drift.
  • Excellent communication and storytelling skills, with an ability to translate complex technical architectures and probabilistic model behaviors to executive finance leadership.