Applied AI/ML Lead

JPMorgan Chase

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Chicago, IL
Posted: 10 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $215k

$170k most similar roles pay here $255k

This listing doesn't post a salary. Most similar roles pay $183,477–$246,150.

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 Lead

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As an Applied AI/ML Lead within the Commercial & Investment Bank Technology team, you will lead large initiatives to solve complex business problems for Wholesale Lending Services. You will collaborate with product owners, data engineers, and software engineers to develop state-of-the-art machine learning and deep learning models for tasks like NLP, personalization, recommendation systems, and information retrieval. Your daily work involves building end-to-end ML/AutoML/AutoNLP pipelines, designing training frameworks, and operationalizing batch and real-time prediction pipelines. You will utilize a technical stack including Python, Java, C/C++, and tools such as Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas. Additionally, you will leverage LLMs like GPT, Claude, and Llama using Prompt Engineering while deploying models on AWS platforms including SageMaker, EC2, and Glue to solve real-world problems in a complex data landscape.

Skills

Machine Learning Deep Learning LLMs Generative AI NLP Python Java C++ Hugging Face Transformers TensorFlow PyTorch NumPy Scikit-Learn Pandas AWS SageMaker EC2 Glue Prompt Engineering

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, deep learning, and NLP models to solve real-world business problems.
Build end-to-end ML, AutoML, and AutoNLP pipelines for tasks like Document Q&A and information retrieval.
Construct batch and real-time model prediction pipelines integrated with existing applications and front-end systems.
Design experiments and training frameworks while evaluating performance metrics aligned with business goals.
Deploy production-ready models using AWS tools such as SageMaker, EC2, and Glue.
Translate complex technical concepts into clear explanations for senior leaders and non-technical stakeholders.
Develop production-quality code including automated testing and continuous integration components.

What we're looking for

BS, MS, or PhD in Computer Science, Data Science, Statistics, Mathematical sciences, or Machine Learning.
Strong background in Mathematics and Statistics.
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 LLMs such as GPT, Claude, or Llama.
Experience with Prompt Engineering, NLP, and deep learning methods.
Extensive experience with ML toolkits including Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas.
Experience building and deploying ML models on AWS using tools like SageMaker, EC2, and Glue.
Strong communication skills to explain complex technical concepts to both technical and business audiences.