Senior ML Platform Engineer - GPU Training & Cloud

Aumni; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Competitive total rewards

Health care coverage

Equity eligibility

Job summary

JPMorganChase is seeking a Lead Software Engineer for the AI/ML Data Platforms team in Palo Alto. You will design, build, and operate scalable ML training systems on AWS and other clouds, focusing on GPU-based workloads, reproducibility, and cost efficiency.

You will enable Gen AI/LLM training, improve observability, and establish enterprise-grade guardrails across environments while collaborating with data engineering and platform teams to raise the standard of AI engineering practices.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Experience running ML training in cloud environments and debugging issues across infrastructure & code.
• Strong Python skills with testing, code reviews, modular design.
• Experience building automation/CI for ML codebases (build, test, release, deployment).
• Hands-on experience with deep learning training workflows (PyTorch or TensorFlow).
• Understanding of training performance, data loading bottlenecks, and reproducibility.
• Experience with distributed training concepts (DDP/FSDP/DeepSpeed) and scaling analyses.
• Ability to profile and optimize training systems (CPU/GPU/utilization).
• Experience with Kubernetes and AWS (EKS, ECR, S3, IAM, VPC).
• Ability to set expectations for validating AI outputs for correctness, performance, and security.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads, improve throughput and reproducibility.
• Build and operate training infra on Kubernetes (EKS) including resource management.
• Enable Gen AI/LLM training and fine-tuning workflows with governance.
• Implement observability for training systems: metrics, logs, dashboards, alerting.
• Collaborate with data engineering and platform teams to define interfaces and guardrails.
• Improve developer experience for training: containers, CI/CD, templates, docs.
• Drive team adoption of enterprise AI-assisted dev practices with secure coding and testing standards.
• Apply SDLC tooling to enhance automation and quality.

Skills

Python

ML training

Kubernetes

AWS

Distributed training

GPU compute

CI/CD

Observability

Security & governance

AI safety

Education

Bachelor's degree in Computer Science or related field

Tools

Kubernetes (EKS)

AWS

PyTorch

TensorFlow

Docker

Job description

JPMorganChase is seeking a Lead Software Engineer for the AI/ML Data Platforms team in Palo Alto. You will design, build, and operate scalable ML training systems on AWS and other clouds, focusing on GPU-based workloads, reproducibility, and cost efficiency.

You will enable Gen AI/LLM training, improve observability, and establish enterprise-grade guardrails across environments while collaborating with data engineering and platform teams to raise the standard of AI engineering practices.