Senior ML Platform Architect

Fairygodboss; New York (NY); On-site; USD 180,000 - 250,000; Full time

Job summary

JPMorgan Chase, within the Consumer & Community Banking (CCB) line, seeks a Senior Lead Software Engineer – ML to join an agile team building, scaling, and maintaining robust machine learning platforms.

You will design and deliver trusted infrastructure and tools to empower data scientists and ML engineers to develop, deploy, and monitor models securely and efficiently across enterprise-grade environments.

Qualifications

• Formal training or certification in software engineering with 5+ years of applied experience.
• Hands-on experience building and maintaining ML platforms or infrastructure.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with data processing (Spark, Pandas, SQL).

Responsibilities

• Design, build, and maintain scalable ML platforms and infrastructure.
• Develop and optimize tools for training, deployment, monitoring, and lifecycle management.
• Integrate data engineering, feature management, and model serving into unified solutions.
• Implement secure, production-grade code for platform services and automation pipelines.
• Collaborate with data scientists, ML engineers, and product teams to deliver platform features.
• Ensure platform reliability, scalability, and performance with proactive monitoring.
• Produce architecture and design artifacts aligned with enterprise standards.
• Automate infra provisioning, configuration, and CI/CD pipelines for ML services.
• Contribute to the ML platform engineering community of practice.

Skills

5+ years software engineering

ML platform

Python

TensorFlow / PyTorch / Scikit-learn

Data processing (Spark / Pandas / SQL)

CI/CD for ML / MLOps

APIs / microservices

Agile methodologies

Tools

PySpark

Docker

Kubernetes

Airflow

Terraform

Job description

JPMorgan Chase, within the Consumer & Community Banking (CCB) line, seeks a Senior Lead Software Engineer – ML to join an agile team building, scaling, and maintaining robust machine learning platforms.

You will design and deliver trusted infrastructure and tools to empower data scientists and ML engineers to develop, deploy, and monitor models securely and efficiently across enterprise-grade environments.