Senior MLOps Lead for Real-Time Personalization

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Senior MLOps Engineer to collaborate with Data Scientists, building and deploying ML models on a modern MLOps stack. You will lead ML engineering on the Recommendation Engine, creating pipelines for distributed training on GPU clusters, model serving at scale, and observability in AWS.

The role emphasizes monitoring, validation, and continuous improvement of infrastructure, with cross-functional collaboration across product and architecture teams."

Qualifications

• BS in Computer Science or related Engineering field with 6+ years of experience or MS degree with 4+ years experience.
• Solid knowledge and extensive experience in Python.
• Deep knowledge and passion for data science fundamentals, training and deploying models.
• Experience in monitoring and observability tools to monitor model input/output and features stats.
• Operational experience in big data/ML tools such as Ray, DuckDB, Spark.
• Solid grounding in engineering fundamentals and analytical mindset.
• Action Oriented and iterative development.

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 learning applications.
• Establish and maintain comprehensive monitoring and observability pipelines to ensure system health, performance, and rapid issue resolution.
• Collaborate with cross-functional teams to integrate new technologies and continuously improve existing infrastructure.
• Partner with product, architecture, and other engineering teams to define scalable and performant technical solutions.

Skills

Python

Data science basics

Model training

Big data fundamentals

Action oriented

Engineering fundamentals

Education

BS in Computer Science or related Engineering field

MS in Computer Science or related Engineering field

Tools

Ray

DuckDB

Spark

Docker

Kubernetes

Airflow

Kubeflow

Job description

JPMorgan Chase & Co. seeks a Senior MLOps Engineer to collaborate with Data Scientists, building and deploying ML models on a modern MLOps stack. You will lead ML engineering on the Recommendation Engine, creating pipelines for distributed training on GPU clusters, model serving at scale, and observability in AWS.

The role emphasizes monitoring, validation, and continuous improvement of infrastructure, with cross-functional collaboration across product and architecture teams."