Applied AI ML Lead

As an Applied AI ML Lead - Data Scientist- Vice President within the AI/ML team at JPMorgan Chase youll leverage your technical expertise and leadership abilities to support AI innovation. You should have deep knowledge of AI/ML and effective leadership to inspire the team align cross-functional stakeholders engage senior leadership and promote business results.

Job Responsibilities:

• Lead a local AI/ML team with accountability and engagement into a global organization.
• Mentor and guide team members fostering an inclusive culture with a growth mindset.
• Collaborate on setting the technical vision and executing strategic roadmaps to drive AI innovation.
• Deliver AI/ML projects through our ML development life cycle using Agile methodology. Help transform business requirements into AI/ML specifications define milestones and ensure timely delivery.
• Work with product and business teams to define goals and roadmaps. Maintain alignment with cross-functional stakeholders.
• Exercise sound technical judgment anticipate bottlenecks escalate effectively and balance business needs versus technical constraints.
• Design experiments establish mathematical intuitions implement algorithms execute test cases validate results and productionize highly performant scalable trustworthy and often explainable solution.
• Participate and contribute back to firmwide Machine Learning communities through patenting publications and speaking engagements.
• Evaluate and design effective processes and systems to facilitate communication improve execution and ensure accountability.

Required qualifications capabilities and skills:

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• Experience as a hands-on practitioner developing production AI/ML solutions.
• Knowledge and experience in machine learning and artificial intelligence. Ability to set teams up for success in speed and quality and design effective metrics and hypotheses.
• Expert in at least one of the following areas: Large Language Models Natural Language Processing Knowledge Graph Reinforcement Learning Ranking and Recommendation or Time Series Analysis.
• Good understanding ofData structures Algorithms Machine Learning Data Mining Information Retrieval Statistics.
• Experience in advanced applied ML areas such as GPU optimization finetuning embedding models inferencing prompt engineering AI evaluation RAG (Similarity Search).
• Demonstrated expertise in machine learning frameworks: Tensorflow Pytorch pyG Keras MXNet Scikit-Learn.
• Strong programming knowledge of python spark; Strong grasp on vector operations using numpy scipy; Strong grasp on distributed computation using Multithreading Multi GPUs Dask Ray Polars etc.

Preferred qualifications capabilities and skills

• Familiarity in AWS Cloud services.
• Strong people management and team-building skills. Ability to coach and grow talent foster a healthy engineering culture and attract/retain talent. Ability to build a diverse inclusive and high-performing team.
• Ability to inspire collaboration among teams composed of both technical and non-technical members. Effective communication solid negotiation skills and strong leadership.