Applied AI/ML - Vice President

JPMorgan Chase & Co.; Chicago (IL); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. invites an Applied AI/ML Vice President to lead advanced AI initiatives across Wholesale Lending Services within the CIB Technology team.

The role focuses on designing and implementing state-of-the-art ML solutions, including NLP, personalization, and recommendation systems, while collaborating with product, data engineering, and software engineering teams. The ideal candidate will shepherd end-to-end ML/AutoML pipelines, productionize models, and communicate complex

Qualifications

• Master's or Ph.D. in Computer Science, Data Science, Statistics, Mathematical Sciences or Machine Learning.
• 7+ years applying data science and ML techniques to business problems.
• Experience with LLMs and Prompt Engineering.
• 1+ year of GenAI/LLM experience (GPT, Claude, Llama, etc).
• Strong background in NLP, Generative AI, ML and DL methods; familiarity with large language models.
• Experience with ML/DL toolkits (Transformers, HuggingFace, TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).
• Experience with AWS tools (Sagemaker, EC2, Glue).
• Excellent written and verbal communication; ability to work in a cross-functional team.

Responsibilities

• Lead programs and direct large AI/ML initiatives; help product leadership define problems and roadmaps.
• Develop state-of-the-art ML models for NLP, personalization, or recommendation systems.
• Collaborate with business, operations, and tech teams to identify AI needs and devise solutions.
• Build end-to-end ML/AutoML/AutoNLP pipelines and orchestrate model deployment.
• Create batch and real-time model prediction pipelines with app/frontend integrations.
• Lead large-scale data modeling experiments and explain results to senior leaders.
• Collaborate with partner teams to deploy production solutions.
• Productionize models with Product Owners and Software Engineers; align with business stakeholders.
• Foster a culture of recognition and a high-performing team environment.

Skills

Python

LLMs

NLP

Transformers

TensorFlow

PyTorch

HuggingFace

Java

C/C++

AWS Sagemaker

Education

Master's or PhD in Computer Science

Tools

Transformers

HuggingFace

TensorFlow

PyTorch

NumPy

Scikit-Learn

Pandas

AWS Sagemaker

EC2

Glue

Job description

Are you looking for an exciting opportunity to solve exciting business problems? Our Technology team builds innovative products, services, applications to support various business functions, workflows of Wholesale Lending Services.

As an Applied AI/ML Vice President within the Corporate and Investment Bank (CIB) Technology team at JPMorganChase, you will lead the analysis of complex business problems, design and experiment with state‑of‑the‑art models, and develop robust machine learning and deep learning solutions. You will apply your expertise in machine learning toolkits and algorithms to identify, build, and deliver fit‑for‑purpose solutions that promote measurable business impact. As a part of an innovative, cross‑functional team, you will collaborate closely with product owners, data engineers, and software engineers to architect and implement new systems and capabilities. This role is ideal for someone with a strong passion for data, machine learning, and software development, who can navigate and interpret the data landscape of large, complex organizations to unlock actionable insights and scalable AI solutions.

Job Responsibilities

• Lead programs and provide directions to successfully implement the large AI/ML initiatives and assist product leadership in defining the problem statements, execution roadmap
• Develop state‑of‑the‑art machine learning models to solve real‑world problems and apply it to tasks such as NLP, personalization, or recommendation systems.
• Collaborate with business, operations, and other technology colleagues to understand AI needs and devise possible solutions.
• Develop end‑to‑end ML/AutoML/AutoNLP pipelines and operationalize the end‑to‑end orchestration of the ML models to support the various use cases like Document Q&A, Search, Information Retrieval, classification, personalization, etc.
• Build both batch and real‑time model prediction pipelines with existing application and front‑end integrations.
• Collaborate to develop large‑scale data modeling experiments,explain complex concepts to seniorleadersand stakeholders.
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
• Work with Product Owners and Software Engineers to productionize the models and Partners closely with business partners to identify impactful projects, influence key decisions with data, and ensure client satisfaction and deliver regular team updates and maintain full transparency into the team's priorities, progress, and deliverables across stakeholders.
• Champion a culture of recognition by actively celebrating individual and team accomplishments, reinforcing a positive and high‑performing team environment.

Required qualifications, capabilities, and skills

• Master's or Ph.D. in Computer Science, Data Science, Statistics, Mathematical Sciences or Machine Learning with strong background in Mathematics and Statistics.
• 7+ years’ experience in applying data science, ML techniques to solve business problems and one of the programming languages like Python, Java, C/C++, etc.
• Experience with LLMs and Prompt Engineering techniques.
• 1+ year of experience working with Gen AI solutions / LLMs such as GPT, Claude, Llama etc.
• Solid background in NLP, Generative AI and hands‑on experience and solid understanding of Machine Learning and Deep Learning methods and familiar with large language models
• Extensive experience with Machine Learning and Deep Learning toolkits (e.g.: Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit‑Learn, Pandas)
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
• Experience with Big Data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
• Experience with building and deploying ML models on AWS esp. using AWS tools like Sagemaker, EC2, Glue, etc.
• Knowledge of the Active Learning, Agent/Multi Agent Learning, Learning from Supervision/Feedback, etc. Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments.
• Ability to work on tasks and projects through to completion with limited supervision. Passion for detail and follow through. Excellent communication skills and team player

Preferred qualifications, capabilities and skills

• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journals
• Experience with A/B experimentation and data/metric-driven product development
• Ability to develop and debug production-quality code and familiarity with continuous integration models and unit test development