Job
Core
Design, develop, and productionize machine learning models end-to-end for business-critical use cases like churn prediction, fraud detection, and client lifetime value.
Role type
Senior AI/ML Engineer (Applied AI Lead)
Builds
Production-grade AI systems, MLOps pipelines, and model monitoring frameworks for a multi-regulated financial broker.
Domain
Fintech / Financial Services / Machine Learning
Deliverable
production ML models
Required skills
Python, software engineering fundamentals, machine learning concepts, large-scale data processing (Spark/PySpark), ML lifecycle tools (MLflow), CI/CD pipelines, SQL, model deployment and monitoring, model governance and explainability.
Preferred skills
Fintech/trading domain experience, real-time/streaming ML systems, modern AI approaches (LLMs, embeddings, RAG), regulated environment experience.
Technologies
Python, Spark, PySpark, MLflow, GitHub Actions, SQL, SHAP
Responsibilities
Design and deploy end-to-end ML models; lead AI use cases aligned with business outcomes; build MLOps practices and deployment pipelines; implement model monitoring for drift and performance; ensure model explainability and governance; collaborate with Data Engineering on data pipelines; mentor team members.
Seniority
Senior, hands-on IC with leadership responsibilities
