Senior ML Platform Engineer: GPU Training & Cloud Pipelines

JP Morgan Chase; Seattle (WA); On-site; USD 138,000 - 185,000; Full time

Job summary

JPMorganChase seeks a Software Engineer III - Machine Learning Platform to advance scalable ML training systems. You will work on GPU-driven workloads, productionize training, and optimize performance across AWS and cloud environments.

You will contribute to observability, tooling, and developer experience, ensuring governance and security while collaborating in an agile team across Palo Alto, Seattle and other U.S. locations.

Qualifications

• We have formal training or certification on software engineering concepts and 3+ years applied experience.
• Demonstrated experience running ML training in cloud environments and debugging issues across infrastructure and 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 including data loading bottlenecks, mixed precision, checkpointing, reproducibility, and evaluation methodology.
• Experience with distributed training and concepts (DDP/FSDP/DeepSpeed), scaling and bottleneck analysis.
• Ability to profile and optimize training systems (CPU/GPU utilization, memory, I/O, networking, scheduling).
• Experience with Kubernetes fundamentals for running compute-intensive workloads and AWS (EKS/ECR, S3, IAM, VPC) and cloud observability tools.

Responsibilities

• Design, build, and maintain end-to-end ML training platform.
• Run and optimize GPU training workloads (single-node and distributed) to improve throughput and reproducibility.
• Build and operate training infrastructure on Kubernetes and cloud services.
• Enable Gen AI/LLM training and fine-tuning workflows with governance and scalable GPU execution patterns.
• Implement observability for training systems: metrics, logs, dashboards, alerting, and runbooks.
• Partner with data engineering and platform teams to define interfaces, standards, and guardrails.
• Improve developer experience for training: containers, CI/CD, templates, docs, self-service workflows.
• Utilize enterprise AI coding tools with QA via reviews, tests, and secure coding standards.

Skills

Python programming

Cloud ML development

Agile methodologies

GPU training optimization

Debugging/infrastructure

Performance tuning

Code reviews

Experimentation & reproducibility

Education

Formal software engineering training or certification

Tools

PyTorch

TensorFlow

Kubernetes (EKS)

AWS (S3, IAM, VPC)

CI/CD tooling

Distributed training frameworks

Model registry / workflow tools

Job description

JPMorganChase seeks a Software Engineer III - Machine Learning Platform to advance scalable ML training systems. You will work on GPU-driven workloads, productionize training, and optimize performance across AWS and cloud environments.

You will contribute to observability, tooling, and developer experience, ensuring governance and security while collaborating in an agile team across Palo Alto, Seattle and other U.S. locations.