Senior ML Platform Engineer - GPU Training on Cloud

J.P. Morgan; New York (NY); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Tuition reimbursement

On-site wellness

Job summary

JPMorganChase is seeking a Lead Software Engineer to design, build and operate an end-to-end ML training platform. You will run GPU training workloads, scale training, and manage infrastructure on Kubernetes (EKS) across cloud environments.

You will enable Gen AI/LLM training, implement observability, and collaborate with data engineering to enforce security, cost controls and reusable patterns across teams.

Qualifications

• Formal training or certification in software engineering concepts with 5+ years applied experience.
• Demonstrated experience running ML training in cloud environments and debugging across infra & code.
• Strong Python skills with solid engineering practices (testing, code reviews, modular design).
• Experience building automation/CI for ML codebases (build, test, release, deployment/promotion).
• Hands-on experience with deep learning training workflows and at least one major framework (PyTorch or TensorFlow).
• Understanding training performance and stability: data loading, mixed precision, checkpointing, reproducibility.
• Experience with distributed training concepts (DDP/FSDP/DeepSpeed), scaling and bottleneck analysis.
• Ability to profile and optimize training systems (CPU/GPU, memory, I/O, networking, scheduling).
• Experience with Kubernetes fundamentals for running compute-intensive workloads and AWS (EKS/ECR, S3, IAM, VPC, CloudWatch, EC2).
• Strong understanding of responsible AI use and secure adoption within delivery practices.

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: metrics, logs, dashboards, alerting, runbooks.
• Collaborate with data engineering and platform teams to define interfaces and guardrails.
• Improve developer experience with containers, CI/CD, templates, docs, self-service workflow.
• Promote enterprise-authored AI-assisted engineering practices, code reviews and testing.
• Apply SDLC tools with AI-assisted development to improve automation.

Skills

Python

ML training

Kubernetes

AWS

Distributed training

GPU

CI/CD

Security/compliance

Performance optimization

Code reviews

Tools

Kubernetes (EKS)

S3

IAM

VPC

CloudWatch

Job description

JPMorganChase is seeking a Lead Software Engineer to design, build and operate an end-to-end ML training platform. You will run GPU training workloads, scale training, and manage infrastructure on Kubernetes (EKS) across cloud environments.

You will enable Gen AI/LLM training, implement observability, and collaborate with data engineering to enforce security, cost controls and reusable patterns across teams.