Description

Key Responsibilities

• Maintain and develop ML serving pipelines using Kubeflow, Spark, and Python.
• Collaborate with Data Science teams on training pipelines and feature engineering.
• Develop features, deploy applications, perform testing, and implement vulnerability fixes.
• Debug and provide support for production ML pipelines and CI/CD workflows.
• Support integration efforts across various groups and the enterprise.
• Build, train, and deploy machine learning models.
• Support models related to credit card decisioning, fraud tracking, and risk assessment.

Required Qualifications

• Experience with MLOps and ML tooling.
• Proficiency in Python.
• Knowledge of Kubernetes and AWS.
• Experience with Kubeflow or equivalent workflow tools.
• Familiarity with Spark, pandas, and NumPy.

Preferred Qualifications

• Previous experience with the client is desirable.
• Experience with SQL and data analysis.
• Familiarity with Databricks.
• Knowledge of additional ML tooling, such as mlplot.
• Understanding of DevOps concepts, including Jenkins and CI/CD pipelines.
• An AWS Solution Architect Certification is considered an asset

Key Skills

Education

Any Gradute