Lead Machine Learning Engineer-MLOps Vice President

We are looking for a Senior MLOps engineer to work closely with Data Scientists to build and deploy ML models on a modern MLOps stack. As Lead Machine Learning Engineer on the Recommendation Engine team, you’ll build and maintain pipelines for distributed model training on large compute clusters, batch/real-time model serving, hyperparameter tuning at scale, model monitoring, production validation and other activities vital for model development, testing and deployment in a well-managed, controlled environment. Our product, Personalization and Insights, builds and supports high throughput, low latency applications which leverage state of the art machine learning architectures, and which are deployed in AWS.

These applications power personalized experiences across Chase Consumer & Community Banking channels, to help weave a user experience that includes traditional banking services with other services in the Travel, Merchant Offer Shopping, and Dining spaces. Job responsibilities Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters to support scalable machine learning workflows. Develop and manage pipelines for high-throughput, real-time inference as well as batch inference, ensuring optimal performance and reliability.

Implement quantization techniques and deploy large language models (LLMs) to maximize efficiency and resource utilization. Oversee the management and optimization of vector databases to support advanced AI and machine le