This is a unique opportunity to apply your skills and contribute to impactful global business initiatives.
As an Applied AI/ML Lead Vice President at JPMorgan Chase within the Commercial Banking business, you will have the unique opportunity to leverage your technical expertise and leadership abilities to support AI innovation. This role allows you to apply your deep knowledge of AI/ML in a leadership role where you can inspire your team, align with cross-functional stakeholders, engage with senior leadership, and promote impactful 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.
Required qualifications, capabilities, and skills:
- 12+ (BS) or 9+ (MS) or 7+ (PhD) years of relevant in Computer Science, Data Science, Information Systems, Statistics, Mathematics or equivalent experience.
- Track record of managing AI/ML or software development teams.
- Experience as a hands-on practitioner developing production AI/ML solutions.
- Deep 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: Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
- Deep knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
- 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.
- 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.
- Can evaluate and design effective processes and systems to facilitate communication, improve execution, and ensure accountability.
Preferred qualifications, capabilities, and skills:
. Bachelor's degree in a technical or quantitative field with preferred focus on Information Systems
. Familiarity in AWS Cloud services such as EMR, Sagemaker etc.,
