Applied AI/ML Vice President

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Chicago, IL
Posted: 11 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $200k

$130k most similar roles pay here $254k

This listing doesn't post a salary. Most similar roles pay $157,200–$242,000.

Based on 240 similar postings.

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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 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Applied AI/ML Vice President

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As an Applied AI/ML - Vice President within the Corporate and Investment Bank Technology team, you will lead the analysis of complex business problems while designing and experimenting with state-of-the-art machine learning and deep learning solutions. You will build end-to-end ML, AutoML, and AutoNLP pipelines to support use cases like Document Q&A, search, information retrieval, classification, and personalization. Collaborating with cross-functional teams including product owners and software engineers, you will develop batch and real-time prediction pipelines for Wholesale Lending Services. The role requires expertise in Python, Java, or C/C++, along with experience in LLMs, Prompt Engineering, and tools such as Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas. You will also utilize AWS services like SageMaker, EC2, and Glue to deploy scalable models within a complex data landscape.

Skills

Machine Learning Deep Learning Generative AI LLMs NLP Python Java C++ Transformers Hugging Face TensorFlow PyTorch NumPy Scikit-Learn Pandas AWS SageMaker Prompt Engineering Big Data

What you'll do

Lead large AI/ML initiatives by defining problem statements and execution roadmaps for product leadership.
Develop state-of-the-art machine learning models for tasks like NLP, personalization, and recommendation systems.
Build end-to-end ML, AutoML, and AutoNLP pipelines to operationalize model orchestration for various use cases.
Construct both batch and real-time model prediction pipelines with existing application and front-end integrations.
Design large-scale data modeling experiments and explain complex technical concepts to senior leaders and stakeholders.
Partner with cross-functional teams to productionize models and ensure solutions meet business requirements.
Deploy scalable machine learning models using cloud infrastructure such as AWS SageMaker, EC2, and Glue.

What we're looking for

Master's or Ph.D. in Computer Science, Data Science, Statistics, Mathematical Sciences, or Machine Learning.
7+ years of experience applying data science and ML techniques to solve business problems using Python, Java, C/C++, or other programming languages.
At least 1 year of experience working with Generative AI solutions and Large Language Models such as GPT, Claude, or Llama.
Expertise in NLP, Generative AI, and deep learning methods including Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas.
Experience with Prompt Engineering techniques and large-scale data modeling experiments.
Proficiency in building and deploying ML models on AWS using tools like SageMaker, EC2, and Glue.
Ability to design training frameworks and evaluate model performance metrics aligned with business goals.
Strong communication skills to explain complex technical concepts to both technical and non-technical stakeholders.

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