Lead ML Platform Engineer - GPU & Cloud

JPMorgan Chase; Palo Alto (CA); On-site; USD 157,000 - 215,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer - Machine Learning in Palo Alto to architect scalable ML training platforms on AWS and other clouds. You will push GPU-based workloads, optimize performance, and own end-to-end pipelines within a fast-moving AI/ML Data Platforms team.

Responsibilities include building training infra on Kubernetes, enabling Gen AI workflows, and delivering governed, reproducible experiments. Strong Python, deep learning, and CI/CD capabilities are required.

Qualifications

• Formal training or certification on software engineering concepts is required.
• 5+ years of applied software engineering experience in ML or cloud environments.
• Deep learning frameworks (PyTorch or TensorFlow) experience.
• Experience building automation/CI for ML codebases and training workloads.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads and distributed training.
• Operate training infrastructure on Kubernetes and AWS cloud services.
• Enable GenAI/LLM training workflows with governance and security.
• Implement observability with metrics, logs, dashboards and runbooks.
• Collaborate with data engineering to define interfaces and guardrails.
• Improve developer experience with containers, templates, and self-service workflows.
• Promote AI-assisted engineering practices and standardized validation.

Skills

Python

ML training in cloud

Kubernetes

AWS

PyTorch

TensorFlow

CI/CD

Observability

Secure coding

AI governance

Education

Software engineering training/certification

Tools

Kubernetes (EKS)

S3

IAM

CI/CD tooling

Job description

JPMorganChase is seeking a Lead Software Engineer - Machine Learning in Palo Alto to architect scalable ML training platforms on AWS and other clouds. You will push GPU-based workloads, optimize performance, and own end-to-end pipelines within a fast-moving AI/ML Data Platforms team.

Responsibilities include building training infra on Kubernetes, enabling Gen AI workflows, and delivering governed, reproducible experiments. Strong Python, deep learning, and CI/CD capabilities are required.