Lead ML Engineer: Scalable Production AI

JPMorgan Chase; Palo Alto (CA); On-site; USD 171,000 - 260,000; Full time

Job summary

JPMorgan Chase is seeking a Lead Machine Learning Engineer for its Digital Intelligence team. The role focuses on building scalable ML pipelines, distributed model training on GPU clusters, and evaluating modern LLM-based methods where appropriate.

You will collaborate with software developers and deep learning experts to deploy, monitor, and improve ML models in production, ensuring reliability and security across platforms.

Qualifications

• BS in Computer Science or related Engineering field with 6+ years of experience or MS degree with 4+ years of experience.
• Strong Python and cloud computing skills, with experience in ML frameworks (PyTorch, TensorFlow).
• Deep knowledge of data science fundamentals, training and deploying models.
• Experience with monitoring/observability tools for model input/output and features stats.
• Experience with big data/ML tools like Ray and Spark; training and inference systems.
• Solid engineering fundamentals and enterprise system design knowledge.

Responsibilities

• Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters.
• Develop and manage pipelines for model promotion and MDLC-related capabilities.
• Optimize training throughput for large data sources.
• Establish integrations to platforms/tools for model monitoring and observability.
• Collaborate with cross-functional teams to integrate new technologies into the ML platform.
• Partner with product, architecture, modeling, and engineering to power digital channels.

Skills

Python

Cloud computing

ML frameworks

Model monitoring

Distributed training

Ray & Spark

Docker & Kubernetes

Airflow/Kubeflow

CUDA

Education

BS in Computer Science or related Engineering

MS in Computer Science or related Engineering

Tools

PyTorch

TensorFlow

Ray

Spark

Docker

Kubernetes

Airflow

Kubeflow

vLLM / SGLang

Job description

JPMorgan Chase is seeking a Lead Machine Learning Engineer for its Digital Intelligence team. The role focuses on building scalable ML pipelines, distributed model training on GPU clusters, and evaluating modern LLM-based methods where appropriate.

You will collaborate with software developers and deep learning experts to deploy, monitor, and improve ML models in production, ensuring reliability and security across platforms.