below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$179,475–$246,475.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1262 open roles
on FindRole.
Listed pay typically runs
$150,433–$215,000
across 11 roles with salary data.
As a Personalization Product Manager - Machine Learning Platform - Vice President within the Personalization & Customer Insights team, you will shape the vision and own the roadmap for the model development lifecycle. You will drive execution across Data Science, ML Engineering, Cloud, and Infrastructure to make getting models into production fast, repeatable, and safe. Your daily work involves managing serving paths for batch, real-time, and language model hosting while overseeing reporting for performance, monitoring, explainability, and cost. You will utilize SQL, Python, and tools like GitHub Copilot or Claude to solve technical problems. Key responsibilities include building self-serve tooling, managing GPU capacity planning, and ensuring model governance. You must balance new capabilities against reliability and regulatory needs to shorten the time from trained model to production.
Shape the platform strategy and own the roadmap for the model development lifecycle, including deployment, serving, monitoring, and governance.
Shorten the time from trained model to production by creating standardized, self-serve paths that eliminate custom infrastructure work.
Own the roadmap for batch, real-time, and language model hosting, ensuring specific targets for response time, uptime, and cost.
Develop and manage reporting for performance, monitoring, drift, explainability, cost, and service health for model owners and stakeholders.
Define out-of-the-box features for hosted language models, including routing, evaluation, tracing, guardrails, and cost reporting.
Partner with engineering on architecture and build-versus-buy decisions while pressure-testing technical details.
Collaborate with Risk and Compliance to automate governance and regulatory requirements within the platform.
Define and track KPIs such as time to production, adoption, reliability, and cost per inference to justify platform investment.
What we're looking for
5+ years of product management experience or equivalent, including owning the roadmap for a technical or platform product.
Proven success delivering ML platform or MLOps products to production in partnership with ML Engineering, Data Science, and infrastructure teams.
Strong working knowledge of production model operations, including batch and real-time inference, deployment, versioning, monitoring, and cost tradeoffs.
Experience hosting or serving small and large language models, including routing, evaluation, and managing cost and response time.
Track record of measurably shortening time to production through self-serve tooling, standard deployment paths, or automation.
Hands-on data fluency to explore and query data using SQL, Python, or AI-assisted tools.
Proven ability to drive execution across a matrixed organization with excellent stakeholder management and communication skills.
BS or MS in Computer Science, Engineering, Data Science, or a comparable field (preferred).
Machine Learning
Data Science
SQL
Python
AWS
Snowflake
Jira
Tableau
Grafana
Event-Driven Architecture
Product Development Life Cycle
Data Analytics
Experiment Design
User Research
Journey Mapping
Backlog Management
Machine Learning
Deep Learning
Generative AI
LLMs
NLP
Python
Java
C++
PyTorch
TensorFlow
Hugging Face
Transformers
NumPy
Scikit-Learn
Pandas
AWS
SageMaker
EC2
Glue
Prompt Engineering
Big Data
Data Analytics
Machine Learning
LLM
Data Governance
Product Development Life Cycle
A/B Testing
Dimensional Modeling
Data Discovery
Product Roadmap
User Stories
Responsible AI
AI
LLMs
NLU
Product Development Life Cycle
Agile
Scrum
Data Analytics
Responsible AI
Automation
Telemetry
Metrics
Product Roadmap
Requirements Definition
Software Delivery Lifecycle