Senior ML Platform Engineer: GPU Training & Cloud Infra

JPMorgan Chase & Co.; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorganChase is seeking a Lead Software Engineer in the AI/ML Data Platforms group to design, build, and operate scalable ML training systems on AWS and Kubernetes. You will drive GPU-based training pipelines, performance optimizations, and governance across environments.

You will partner with data engineering and platform teams, improve developer experience with reusable containers and CI/CD, and advance Gen AI/LLM workflows while upholding secure, compliant practices.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Demonstrated experience running ML training in cloud environments and debugging issues across infrastructure & code.
• Strong Python skills with solid engineering practices (testing, code reviews, modular design, dependency management).
• Experience building automation/CI for ML codebases (build, test, release, deployment/promotion workflows).
• Hands on experience with deep learning training workflows and at least one major framework (e.g., PyTorch or TensorFlow).
• Understanding of training performance and stability: data loading bottlenecks, mixed precision, checkpointing, reproducibility, and evaluation methodology.
• Experience with distributed training and related concepts (e.g., DDP/FSDP/DeepSpeed concepts, collective communication basics).
• Ability to profile and optimize training systems (CPU/GPU utilization, memory, I/O throughput).
• Experience with Kubernetes fundamentals for running compute-intensive workloads and AWS (EKS/ECR, S3, IAM, VPC).
• Demonstrated experience leading effective use of AI-assisted development tools with ability to set team expectations for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations and secure handling.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads (single-node and distributed).
• Build and operate training infrastructure on Kubernetes (EKS and others).
• Enable Gen AI/LLM training and fine-tuning workflows with governance.
• Implement observability for training systems: metrics, logs, dashboards, alerts.
• Partner with data engineering and platform teams to define interfaces and guardrails.
• Improve developer experience for training: standardized containers, CI/CD, templates, docs, self-service workflows.
• Drive team adoption of enterprise AI-assisted engineering practices for code quality and automation.
• Apply SDLC toolchain knowledge to improve automation value.

Skills

Python

ML/AI systems

Distributed training

Kubernetes

AWS

PyTorch

TensorFlow

CI/CD

Profiling/Optimization

Security/Compliance

Tools

Kubernetes

Docker

EKS

CI/CD tooling

Job description

JPMorganChase is seeking a Lead Software Engineer in the AI/ML Data Platforms group to design, build, and operate scalable ML training systems on AWS and Kubernetes. You will drive GPU-based training pipelines, performance optimizations, and governance across environments.

You will partner with data engineering and platform teams, improve developer experience with reusable containers and CI/CD, and advance Gen AI/LLM workflows while upholding secure, compliant practices.