Applied Artificial Intelligence​/Machine Learning Lead - Vice President

Position: Applied Artificial Intelligence/ Machine Learning Lead - Vice President
:

Category:
Predictive Science

Job Schedule:

Full time

Posted Date: T14:32:08+00:00

Job Shift:

Base Pay/Salary:
Jersey City,NJ $-$

As an Applied AI/ML Vice President within Global Private Bank, you'll own the full lifecycle of high-impact models serving clients across wealth management, lending, and advisory, from problem framing with business stakeholders to production deployment 'll work on some of the most data-rich, complex client problems in financial services, with the infrastructure and resources of one of the world's largest institutions behind you.

We're building AI-native capabilities at the intersection of cutting-edge research and real-world impact.

Job Responsibilities:

* Define and scope AI/ML problem statements in partnership with Private Bank business leads, translating ambiguous client or operational pain points into tractable modeling problems

* Design, build, and deploy end-to-end ML solutions - including generative AI, NLP, and classical machine learning- across client service, risk, and operational efficiency use cases

* Own model quality, evaluation frameworks, monitoring, drift detection, and iteration post-deployment

* Drive productionization and MLOps practices in collaboration with engineering, working across distributed data infrastructure

* Stay current on applied research; evaluate and adapt emerging techniques - new architectures, agentic frameworks, multimodal models - for relevance to the Private Bank's problem space and translate promising work into production-ready solutions

* Mentor junior data scientists and help set technical standards for the team

* Collaborate across JPMorgan

Chase's broader AI/ML community, model risk, compliance, and peer LOBs to align on standards, share learnings, and amplify the team's impact firm-wide

Required qualifications, capabilities, and skills:

* Master's or PhD in Computer Science, Statistics, Applied Math, Data Science, or related quantitative field

* Atleast 5 years of hands-on ML experience in production environments.

* Deep expertise in NLP, including modern LLM fine-tuning, RAG pipelines, prompt engineering and the design and deployment of multi-step AI agents

* Strong Python skills; proficiency with PyTorch, Tensor Flow, Scikit-learn and other libraries

* Experience with large-scale data processing:
Spark, Hive, SQL

* Proven ability to communicate technical work to non-technical stakeholders

Preferred qualifications, capabilities, and skills:

* Financial services experience