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.
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