Staff ML Engineer: Credit Risk & Production ML

United States Digital Space LLC; San Francisco (CA); On-site; USD 297,000 - 401,000; Full time

Benefits offered by this job

RSUs

Job summary

the company is building a Machine Learning Engineering team in San Francisco focused on Credit Risk Modeling for Underwriting within Financial Products. This team will develop the models, scorecards, and production systems that enable the company to scale its credit products 100x.

As a Staff Machine Learning Engineer you will design, productionize, and operate machine learning models and rule-based decision systems that power credit products.

Qualifications

• 8+ years of machine learning engineering experience.
• Strong Python programming and Java experience.
• End-to-end ML model lifecycle in production.
• Experience processing big data to feed models.
• Understanding of software engineering and MLOps.
• Knowledge of data science, statistics, ML techniques.
• Familiarity with Python data science tools.
• Experience with ML infrastructure (K8s, Docker, Airflow).
• Ability to communicate complex results to diverse audiences.

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 (memory consumption, online latency, training time).
• Collaborate with software engineers to integrate ML solutions into products and services.
• Collaborate with CreditOps and data teams to integrate effectively with current tools, and shape priority for future tools.
• Support and encourage good engineering practices on product ML teams.

Skills

Python

Java

ML lifecycle in production

Big data pipelines

MLOps

Data science concepts

PySpark / Spark

TensorFlow / PyTorch

XGBoost / LightGBM

Pandas

MLFlow

Airflow

Kubernetes / Docker

Stakeholder communication

Tools

PySpark

SQL

TensorFlow

PyTorch

XGBoost

LightGBM

Pandas

MLFlow

Airflow

Kubernetes

Docker

Job description

the company is building a Machine Learning Engineering team in San Francisco focused on Credit Risk Modeling for Underwriting within Financial Products. This team will develop the models, scorecards, and production systems that enable the company to scale its credit products 100x.

As a Staff Machine Learning Engineer you will design, productionize, and operate machine learning models and rule-based decision systems that power credit products.