Software Engineer III - Machine Learning Platform

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorganChase within the AI/ML data platform team you serve as a seasoned member of an agile team to build and operate scalable, reliable ML training systems and pipelines on AWS and other cloud platforms. You will productionize training workloads (often GPU-based), improve performance and cost efficiency, and enable repeatable, well-governed training across environments

Job Responsibilities

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Design, build, and maintain end-to-end ML training platform.

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Run and optimize GPU training workloads (single-node and distributed), improving throughput, utilization and reproducibility.

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Build and operate training infrastructure on Kubernetes (e.g., EKS and other manage Kubernetes platforms), including resource management and workload troubleshooting.

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Enable Gen AI/LLM training and fine-tuning workflows (e.g., supervised fine-tuning), including evaluation harnesses, artifact/version governance, and scalable GPU execution patterns aligned to enterprise controls.

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Implement observability for training systems: metrics, logs, dashboards, alerting, and operational runbooks.

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Partner with data engineering and platform teams to define interfaces, standards, and guardrails (security, access, cost controls)

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Improve developer experience for training: standardized containers, CI/CD, templates, documentation, and self-service workflow

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Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.

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Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

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Formal training or certification on software engineering concepts and 3+ years applied experience

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Demonstrated experience running ML training in cloud environments and debugging issues across infrastructure & code.