Senior MLOps Engineer – Real-Time ML & Personalization

Aumni; Jersey City (NJ); On-site; USD 150,000 - 230,000; Full time

Job summary

Chase is seeking a Senior MLOps Engineer to collaborate with Data Scientists and build a modern MLOps stack for the Personalization and Insights product. You will lead distributed training pipelines on GPU clusters, real-time and batch inference, and model monitoring in AWS environments.

You will work with cross-functional teams, define scalable ML solutions, and contribute to production validation and deployment within a controlled environment.

Qualifications

• BS in Computer Science or related Engineering field with 6+ years of experience or MS 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-timeInference 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 programming

Data science fundamentals

Ray

DuckDB

Spark

Docker

Kubernetes

Airflow

Kubeflow

AWS

Monitoring/observability

Education

BS in Computer Science or related Engineering

MS in Computer Science or related Engineering

Tools

GPUs clusters

Job description

Chase is seeking a Senior MLOps Engineer to collaborate with Data Scientists and build a modern MLOps stack for the Personalization and Insights product. You will lead distributed training pipelines on GPU clusters, real-time and batch inference, and model monitoring in AWS environments.

You will work with cross-functional teams, define scalable ML solutions, and contribute to production validation and deployment within a controlled environment.