Senior ML Engineer - Scalable AI Systems & Production DL

JPMorganChase; New York (NY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Chase is seeking a Lead Machine Learning Engineer on the Digital Intelligence team in the US. You will build and maintain distributed model training pipelines on GPU clusters, optimize throughput, and drive observability across training and deployment stages.

You'll collaborate with software engineers and data scientists to advance ML capabilities for Chase's digital channels and customer experiences. Strong Python, cloud, and ML framework experience are required.

Qualifications

• BS in Computer Science or related Eng with 6+ years of experience Or MS in CS with 4+ years.
• Strong Python and cloud computing experience with 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.
• Operational experience with big data/ML tools (Ray, Spark) and training/inference systems (Ray, vLLM/SGLang).
• Solid grounding in engineering fundamentals and enterprise system design.

Responsibilities

• Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters to support scalable ML workflows.
• Develop and manage pipelines for model promotion and MDLC-related capabilities.
• Optimize training throughput for large data sources.
• Establish and maintain integrations to platforms and tools for model monitoring and observability.
• Collaborate with cross-functional teams to integrate new technologies and improve the ML Platform.
• Partner with product, architecture, modeling, and engineering to design robust solutions powering Digital channels.

Tools

Python

Cloud computing

PyTorch

TensorFlow

Data science fundamentals

Monitoring/Observability

Ray

Spark

Docker

Kubernetes

Airflow

Kubeflow

Data storage

Job description

Chase is seeking a Lead Machine Learning Engineer on the Digital Intelligence team in the US. You will build and maintain distributed model training pipelines on GPU clusters, optimize throughput, and drive observability across training and deployment stages.

You'll collaborate with software engineers and data scientists to advance ML capabilities for Chase's digital channels and customer experiences. Strong Python, cloud, and ML framework experience are required.