Senior ML Engineer - Credit Risk & Scalable Finance

United States Digital Space LLC; San Francisco (CA); On-site; USD 228,000 - 317,000; Full time

Job summary

the company in San Francisco leads the development of financial-technology solutions. As a Senior Machine Learning Engineer, you will design, productionize, and operate ML models and rule-based systems powering credit products for global scale.

You will work across the full model lifecycle—from research and data analysis to training, deployment, monitoring, and continuous improvement—balancing innovation with robustness and explainability.

Qualifications

• 5-7+ years of experience as an engineer in the machine learning domain.
• Strong Python programmer with Java experience.
• Experience with full ML model lifecycle in production environments.
• Experience leveraging big data to feed ML models.
• Strong software, data engineering and MLOps practices.

Responsibilities

• Develop and maintain scalable production ML pipelines for feature engineering, model training, validation and deployment.
• Identify and fix performance bottlenecks in ML training and inference.
• Collaborate with software engineers to integrate ML into products and services.
• Collaborate with CreditOps and data teams to align with current tools.
• Promote good engineering practices on product ML teams.

Skills

Python

Java

ML lifecycle

Big data

MLOps

Data analysis

Tools

Kubernetes

Docker

Airflow

Spark/PySpark

TensorFlow

PyTorch

XGBoost/LightGBM

Pandas

MLFlow

Job description

the company in San Francisco leads the development of financial-technology solutions. As a Senior Machine Learning Engineer, you will design, productionize, and operate ML models and rule-based systems powering credit products for global scale.

You will work across the full model lifecycle—from research and data analysis to training, deployment, monitoring, and continuous improvement—balancing innovation with robustness and explainability.