Senior ML Platform Engineer — GPU Training on Cloud

J.P. Morgan; New York (NY); On-site; USD 140,000 - 200,000; Full time

Job summary

JPMorganChase is seeking a Software Engineer III to join the AI/ML data platform team in New York. You will build and operate scalable ML training systems on AWS and other clouds, optimize GPU workloads, and enable repeatable, governed training across environments.

You will leverage Kubernetes, CI/CD, and enterprise AI tooling to improve code quality, delivery speed, and observability, while partnering with data engineering and platform teams to define interfaces and guardrails.

Qualifications

• Formal training or certification in software engineering concepts and 3+ 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, scaling and bottleneck analysis).
• Ability to profile and optimize training systems (CPU/GPU utilization, memory, I/O throughput, networking, scheduling).
• Experience with Kubernetes fundamentals for running compute-intensive workloads and AWS (e.g., EKS/ECR, S3, IAM, VPC/networking, Cloudwatch, EC2).
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment with demonstrated ability to evaluate outputs for correctness, performance, and security.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads (single-node and distributed), improving throughput and reproducibility.
• Build and operate training infrastructure on Kubernetes (EKS and other platforms).
• Enable Gen AI/LLM training workflows with evaluation harnesses, governance, and scalable GPU execution patterns.
• Implement observability for training systems: metrics, logs, dashboards, alerting.
• Partner with data engineering and platform teams to define interfaces, standards, and guardrails (security, access, cost controls).
• Improve developer experience for training: standardized containers, CI/CD, templates, documentation.
• Leverage enterprise AI coding assist tools to improve code quality and productivity, with peer review and secure coding.
• Apply SDLC toolchain knowledge to improve automation.

Skills

Python

ML deployment

Performance optimization

Observability

Code reviews

Testing

Security & governance

Tools

AWS

Kubernetes

Docker

EKS

PyTorch

TensorFlow

CI/CD for ML

Git

Job description

JPMorganChase is seeking a Software Engineer III to join the AI/ML data platform team in New York. You will build and operate scalable ML training systems on AWS and other clouds, optimize GPU workloads, and enable repeatable, governed training across environments.

You will leverage Kubernetes, CI/CD, and enterprise AI tooling to improve code quality, delivery speed, and observability, while partnering with data engineering and platform teams to define interfaces and guardrails.