Applied AI ML Lead

As an Applied AI ML Lead - Data Scientist- Vice President at JPMorgan Chase within the Commercial & Investment Bank's Global Banking team, 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 drive 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.
• Mentor junior team members delivering successful projects and building successful career in the firm.
• 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

• 14+ years (BE/BTech/BS) or 8+ (ME/MTech/MS) or 5+ (PhD) years of relevant experience in Computer 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.
• 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.
• Must have good knowledge on agentic patterns and relevant frameworks, such as LangChain, LangGraph, Auto-GPT etc.
• Strong understanding of AI implementation in software development and legacy code transformation.
• 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 such as EMR, Sagemaker 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.