
Senior AI Architect
16 hours ago
About the Role: Job Overview
You will work on ensuring machine learning products and credit risk policies scale within pre-approved campaigns and live digital journeys. Your tasks will include ensuring APIs operate smoothly at scale, identifying ways to simplify and minimize customer journey risks.
Team Description
You will be part of the Machine Learning Engineering Team within Digital Banking. You will collaborate with teams across Digital and the bank, including data engineers, data scientists, product managers, and senior business and credit risk stakeholders.
Education, Experience, and Key Skill Set Requirements
Education: A Masters or undergraduate degree in Computer Science, Electrical, Civil, or Mechanical engineering is required.
Experience: 6-8 years of industry experience, with at least 3-4 years in Machine Learning (ML) or Business Rule Engine (BRE) implementation is essential.
Technical Expertise:
- End-to-end system architecture design for ML/MLOps systems, including model/BRE implementation, debugging, and production maintenance.
- Programming skills in Python, PySpark, NumPy, Pandas, SQL, and Linux are necessary.
- Hands-on experience with Azure cloud services, including Azure Databricks, Spark, Data Warehousing, and pipeline orchestration is a must.
- Azure DevOps for CI/CD pipeline setup and management, including automated model deployment.
- FastAPI or Flask for building scalable machine learning models APIs is required.
Domain Knowledge:
- Exposure to credit risk modeling and financial services is beneficial.
Soft Skills:
- Excellent communication and stakeholder management.
- Strong project management and cross-functional collaboration abilities.
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