Senior ML Platform Engineer - GPU Training & Cloud Infra

JP Morgan Chase; Jersey City (NJ); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorganChase in Jersey City seeks a Software Engineer III to advance scalable ML training systems on AWS and other clouds. You will productionize GPU workloads, improve performance, and enable repeatable, governable training across environments.

You will build end-to-end training pipelines, optimize Kubernetes deployments, and contribute to observability, security, and developer productivity within an agile team. This is a full-time role in our AI/ML data platform team.

Qualifications

• Formal training or certification on software engineering concepts and 3+ 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, 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 (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 (DDP/FSDP/DeepSpeed), 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 (EKS/ECR, S3, IAM, VPC/networking, CloudWatch, EC2)
• Hands-on experience using enterprise-authorized AI-assisted software development tools with ability to evaluate outputs for correctness, performance, and security.
• Understanding of responsible AI use in engineering workflows, data sensitivity, secure handling, resiliency and security practices.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads, improving throughput, utilization and reproducibility.
• Build and operate training infrastructure on Kubernetes (EKS) including resource management and troubleshooting.
• Enable Gen AI/LLM training and fine-tuning workflows with evaluation harnesses and governance.
• Implement observability for training systems: metrics, logs, dashboards, alerting, and runbooks.
• Partner with data engineering and platform teams to define interfaces, standards, and guardrails (security, cost controls).
• Improve developer experience for training: standardized containers, CI/CD, templates, documentation, and self-service workflow.
• Leverages enterprise-authorized AI coding assist tools to improve code quality and productivity with peer review and automated testing.
• Applies SDLC toolchain knowledge to enhance automation and outputs.

Skills

Python

AWS

Kubernetes

GPU training

ML pipelines

CI/CD

Testing practices

Security awareness

Observability

Peer review

Tools

EKS

S3

IAM

VPC/networking

CloudWatch

Docker

Git

Job description

JPMorganChase in Jersey City seeks a Software Engineer III to advance scalable ML training systems on AWS and other clouds. You will productionize GPU workloads, improve performance, and enable repeatable, governable training across environments.

You will build end-to-end training pipelines, optimize Kubernetes deployments, and contribute to observability, security, and developer productivity within an agile team. This is a full-time role in our AI/ML data platform team.