onsite
Senior Machine Learning Engineer - Credit - Plaid
ML Engineer
Lead the design, development, and deployment of credit risk machine learning models, leveraging Python, deep learning frameworks, and cloud infrastructure to deliver scalable, data‑driven solutions for financial products.
About the role
Key Responsibilities
- Design, build, and productionize credit risk models using Python, TensorFlow, PyTorch, and Scikit-learn.
- Develop end‑to‑end data pipelines for feature extraction, transformation, and validation across large‑scale financial datasets.
- Collaborate with product, data engineering, and security teams to integrate models into APIs and real‑time decisioning systems.
- Monitor model performance, conduct bias and fairness analyses, and implement continuous improvement processes.
- Optimize model training and inference workloads on AWS services, ensuring cost‑effective scalability.
Requirements
- 5+ years of professional experience building and deploying machine learning models in production, preferably in credit or financial services.
- Strong proficiency in Python and deep learning libraries such as TensorFlow or PyTorch.
- Hands‑on experience with data engineering tools, SQL, and cloud platforms (AWS, SageMaker, Lambda, etc.).
- Solid understanding of statistical modeling, feature engineering, and model evaluation techniques for credit risk.
- Excellent problem‑solving skills, ability to work cross‑functionally, and strong communication of technical concepts to non‑technical stakeholders.
Skills
pythontensorflowpytorchawssql