Python FastAPI Engineer for Machine Learning and Risk Modeling

Role: Python FastAPI Engineer (ML & Risk Modeling)

Location: 100% Remote (United States)

Compensation: $50/hr (W2)

Duration: 6 Months

Position Overview

We are seeking a Python FastAPI Engineer to design and operate scalable REST APIs that serve machine learning-driven risk models (e.g., PD/LGD risk rating). This role is critical for bridging the gap between data science and production, focusing on real-time scoring for loans/customers, batch scoring pipelines, and robust model governance.

Key Responsibilities

* API Development: Design and develop high-performance REST APIs using FastAPI for real-time and batch model scoring.

* ML Integration: Support model hosting and execution environments (e.g., SageMaker) and ensure flexible deployment patterns for Python-based models.

* Model Governance: Implement operational capabilities including versioning/lineage, audit trails, and explainability/reason codes.

* Observability & MLOps: Build monitoring pipelines for performance, availability, and model drift using structured logging, metrics, and tracing.

* Testing & Quality: Ensure strong input validation, error handling, and solid engineering practices via unit/integration testing and CI/CD.

Required Qualifications

* Core Skills: Strong hands-on experience with Python and FastAPI (building production-grade services).

* MLOps Experience: Proven experience serving or integrating ML models in production (Risk scoring, classification, or regression).

* Cloud & Tools: Experience with AWS (SageMaker preferred), Git-based workflows, and OpenAPI/Swagger documentation.

* Governance Knowledge: Familiarity with model lineage, version control, and explainability hooks.

* Testing: Mastery of unit/integration testing and CI/CD pipelines.