Python FastAPI Engineer (ML + Risk Modeling)

Job Summary

We are seeking a Python FastAPI Engineer to build and operate scalable API services supporting machine learning-driven risk models such as PD, LGD, and risk rating systems. The role focuses on developing real-time scoring APIs, batch scoring pipelines, and ensuring production readiness through monitoring, logging, and model governance. The engineer will integrate ML models into production environments and enable secure, scalable deployments.

Location

Remote

Experience

8-10 Years

Key Responsibilities

• Design and develop REST APIs using Python and FastAPI for real-time and batch model scoring.
• Integrate machine learning models into production environments for risk scoring and predictive analytics.
• Build secure integrations with upstream and downstream systems ensuring input validation and error handling.
• Support model hosting and execution for Python-based models with flexible deployment strategies.
• Implement model operational capabilities including versioning, lineage tracking, audit trails, and explainability mechanisms.
• Enable observability through structured logging, metrics, tracing, and monitoring.
• Support model performance monitoring and drift detection pipelines.

Required Skills & Experience

• Strong hands-on experience with Python and FastAPI for building production-grade REST services.
• Experience integrating or serving machine learning models in production environments.
• Experience with risk modeling, classification, regression, or predictive analytics systems.
• Strong knowledge of API development including OpenAPI and Swagger documentation.
• Experience with CI/CD pipelines, Git-based workflows, and testing frameworks (unit and integration testing).
• Familiarity with model governance concepts such as version control, lineage tracking, monitoring, explainability, and audit logs.
• Experience with cloud platforms such as AWS and model execution environments like SageMaker.

Competencies

• Strong problem-solving and analytical thinking skills.
• Ability to work in collaborative Agile environments.
• Strong ownership and accountability for deliverables.
• Excellent communication and documentation skills.
• Ability to design scalable and reliable API-based systems.

Preferred Skills

• Experience with financial risk modeling systems (PD, LGD, credit risk scoring).
• Experience implementing model monitoring or drift detection pipelines.
• Knowledge of distributed systems and scalable ML deployment architectures.
• Experience working with data science teams to operationalize machine learning models.