Applied AI/ML - Vice President
On-site · Chicago, Illinois, United States
Job Summary
Vice President, Applied AI/ML leading large AI/ML initiatives within JPMorganChase. Lead programs, assist product leadership in defining problem statements and execution roadmaps, develop state-of-the-art ML models for tasks such as NLP, personalization, or recommendation systems, and build end-to-end ML/AutoML/AutoNLP pipelines. Responsible for productionizing models, collaborating with product owners, data engineers, software engineers, and business partners, and communicating progress to senior leaders. Champion a high-performing team culture and drive cross-functional collaboration across Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management. Skills include deep knowledge of ML/DL, NLP, Gen AI, LLMs, ML toolkits (Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas), AWS (SageMaker, EC2, Glue), experimentation design, and ability to translate data insights into business impact.
Required Qualifications
- BS or MS or PhD in Computer Science or Data Science or Statistics or Mathematical sciences or Machine Learning
- 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.
- Have good understanding about 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
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