Lead ML Training Platform Engineer

JPMorgan Chase & Co.; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. in Palo Alto is seeking a Lead Software Engineer to design, build, and operate a scalable ML training platform on AWS and other cloud platforms. You will optimize GPU training workloads, improve throughput, and drive reproducible training across environments.

You will collaborate with data engineering and platform teams, implement observability, and align with enterprise security and governance. Strong Python, Kubernetes, and cloud experience are required.

Qualifications

• Formal training or certification on software engineering concepts.
• 5+ years applied software engineering experience.
• Strong Python programming skills and engineering practices (testing, reviews).
• Experience running ML training in cloud environments and debugging infrastructure & code issues.
• Experience with distributed training and related concepts (DDP/DeepSpeed).
• Experience with Kubernetes for compute-intensive workloads and AWS (EKS, S3).
• Knowledge of responsible AI practices and secure coding guidelines.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads, improving throughput and reproducibility.
• Build and operate training infrastructure on Kubernetes (EKS) and cloud platforms.
• Enable Gen AI/LLM training and fine-tuning workflows with governance.

Education

Software engineering training

Tools

Python

Kubernetes

AWS

PyTorch

TensorFlow

CI/CD

Observability

Job description

JPMorgan Chase & Co. in Palo Alto is seeking a Lead Software Engineer to design, build, and operate a scalable ML training platform on AWS and other cloud platforms. You will optimize GPU training workloads, improve throughput, and drive reproducible training across environments.

You will collaborate with data engineering and platform teams, implement observability, and align with enterprise security and governance. Strong Python, Kubernetes, and cloud experience are required.