Senior Lead AI/ML Platform Engineer

JPMorgan Chase; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Senior Lead Software Engineer to design, build, and operate foundational cloud infrastructure enabling data scientists and ML engineers.

You will lead platform reliability, scalability, and automation across cross-functional teams to accelerate AI/ML capabilities and production-grade deployments. Responsibilities include creating reusable AI/ML platform services, deploying secure cloud environments with GPU workloads, and driving automation within the SDLC/TLM

Qualifications

• 5+ years of applied software engineering experience.
• Proficient in Python or Java and building production-grade code.
• Strong foundations in distributed systems, microservices, and platform design.
• Experience with cloud-native infra on AWS and other clouds; IaC tooling.

Responsibilities

• Build and maintain scalable AI/ML platform infrastructure and services.
• Deploy and operate secure cloud and container environments for training and inference.
• Design automation and IaC to streamline deployment, provisioning, and release management.
• Develop production-grade APIs, SDKs, and workflows for model training and serving.
• Collaborate with data science and ML teams to translate requirements into platform standards.
• Improve reliability, latency, and cost via orchestration, scheduling, and hardware acceleration.
• Establish monitoring, logging, and incident response best practices.
• Support enterprise AI-assisted tooling and governance across teams.

Skills

Python

Java

Distributed systems

Platform engineering

DevOps

CI/CD

Linux

Scripting

Networking

Education

Formal training or certification in software engineering

Tools

Terraform

Docker

Kubernetes

AWS (EKS)

Kubeflow / MLflow

Job description

JPMorgan Chase & Co. seeks a Senior Lead Software Engineer to design, build, and operate foundational cloud infrastructure enabling data scientists and ML engineers.

You will lead platform reliability, scalability, and automation across cross-functional teams to accelerate AI/ML capabilities and production-grade deployments. Responsibilities include creating reusable AI/ML platform services, deploying secure cloud environments with GPU workloads, and driving automation within the SDLC/TLM