About this role
The Applied AI/ML Lead works in JPMorganChase’s Commercial & Investment Bank Technology team on products and workflows supporting Wholesale Lending Services. The role leads AI/ML initiatives, analyzes business problems, experiments with models, and develops machine learning and deep learning solutions with product owners, data engineers, software engineers, and business partners.
Responsibilities
- Help product leadership define problem statements and execution roadmaps; lead implementation of large AI/ML initiatives.
- Develop models for NLP, personalization, and recommendations. Build and orchestrate end-to-end ML, AutoML, and AutoNLP pipelines for document Q&A, search, information retrieval, classification, and other use cases.
- Build batch and real-time prediction pipelines with application and front-end integrations. Design large-scale modeling experiments and work across business, technology, product, legal, compliance, and other teams to deploy models into production.
- Explain results to senior stakeholders, provide regular updates on priorities and deliverables, and support a collaborative team environment.
Required qualifications
- BS, MS, or PhD in Computer Science, Data Science, Statistics, Mathematical Sciences, or Machine Learning, with a strong mathematics and statistics background.
- At least 7 years applying data science and ML to business problems, with programming experience in a language such as Python, Java, or C/C++.
- At least 1 year working with generative AI solutions or LLMs such as GPT, Claude, or Llama; experience with prompt engineering, NLP, ML and deep learning methods, and toolkits including Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-learn, and Pandas.
- Experience designing experiments and evaluating model performance against business goals, scalable training and big data, and building and deploying ML models on AWS, including SageMaker, EC2, or Glue. Understanding of active learning, agent or multi-agent learning, and learning from supervision or feedback; strong communication and independent and collaborative working skills.
Preferred
Published ML, deep learning, or reinforcement learning research; A/B experimentation and metrics-driven product development; production-quality coding, continuous integration, and unit testing.
The position is full-time in Chicago. The listed Chicago base-pay range is $137,750.00–$235,000.00. Eligible employees may receive incentive compensation and benefits, subject to eligibility.