Applied AI / ML Lead
This role requires a seasoned AI leader to drive innovation at JPMorgan Chase by guiding a team through end-to-end ML project delivery while aligning technical vision with global business goals. The ideal candidate will balance mentorship, strategic execution, and cross-functional collaboration to scale AI solutions across the organization.
Skills required
About this role
As an Applied AI ML Lead - Data Scientist- Vice President within the AI/ML team at JPMorgan Chase, you’ll 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 of Data 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.
