JPMorgan Chase
Lead Machine Learning Engineer-MLOps Vice President
$171K–$260K
Palo Alto, CA +1 · Director · Full-time · Posted Oct 27, 2026
- Location
- Palo Alto, CA
Jersey City, NJ - Experience
- 6+ years with a BS, or 4+ years with an MS.
- Education
- BS in Computer Science or related Engineering field, or MS degree in Computer Science or related Engineering field.
About the job
Build and operate MLOps infrastructure for training, serving, monitoring, and deploying recommendation models and large language models in AWS.
What you'll do
- Build and maintain distributed training pipelines on GPU-enabled clusters and batch and real-time inference pipelines.
- Implement LLM quantization and deployment, and manage vector databases.
- Build monitoring and observability pipelines; collaborate with product, architecture, and engineering teams on scalable solutions.
What they ask for
- BS in Computer Science or a related Engineering field with 6+ years of experience, or MS in Computer Science or a related Engineering field with 4+ years of experience.
- Extensive experience with Python.
- Deep knowledge of data science fundamentals and model training and deployment.
- Experience with monitoring and observability tools, and operational experience with big data/ML tools such as Ray, DuckDB, or Spark.
Nice to have
- Experience with recommendation and personalization systems.
- Experience with containers, Kubernetes or ECS, DAG orchestration tools such as Airflow or Kubeflow, databases, and cloud computing, preferably AWS.
Pay
USD $171,000.00-$260,000.00 base salary (Palo Alto, CA); USD $171,000.00-$260,000.00 base salary (Jersey City, NJ)
Tools
Python, Ray, DuckDB, Spark, Docker, Kubernetes, ECS, Airflow
AI focus
Develop and deploy recommendation models and LLMs, including distributed training, inference, quantization, vector database management, and model monitoring.
Model-written summary · the original posting is authoritative