Applied Artificial Intelligence/ Machine Learning Lead - Vice President

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 150,000 - 200,000; Full time

Job summary

JPMorgan Chase & Co. is hiring an Applied AI/ML Vice President in Jersey City to oversee the lifecycle of impactful models supporting wealth management, lending, and advisory services. The successful candidate will define AI/ML problems, design and deploy solutions, and ensure model quality while collaborating with various teams.

The role requires a Master’s or PhD in a quantitative field and at least 5 years of ML experience. Proven skills in Python and NLP are essential, along with exposure to large-scale data processing tools.

Qualifications

• At least 5 years of hands-on ML experience in production environments.
• Deep expertise in NLP, including modern LLM fine-tuning.
• Proven ability to communicate technical work to non-technical stakeholders.

Responsibilities

• Define and scope AI/ML problem statements with business leads.
• Design, build, and deploy end-to-end ML solutions.
• Own model quality, evaluation frameworks, and monitoring.

Skills

Machine Learning

Natural Language Processing

Python

Data Processing

Education

Master's or PhD in Computer Science, Statistics, Applied Math, or Data Science

Tools

PyTorch

TensorFlow

Scikit-learn

Spark

Hive

SQL

Job description

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 at scale. You'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 JPMorganChase'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, TensorFlow, 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