Applied AI ML Lead

Job Description

We have an exciting and rewarding opportunity for you to take your Predictive Science career to the next level.

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 in 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

- Formal training or certification on Predictive Science concepts and 5+ years applied experience
- Track record of managing AI/ML or software development teams and experience as a hands-on practitioner developing production AI/ML solutions.
- Deep knowledge and experience in machine learning, artificial intelligence and ability to set teams up for success in speed and quality, design effective metrics and hypotheses.
- Expert in at least one of the following areas: Large Language Models, Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
- Good understanding of 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 and strong grasp on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc.
- Familiarity with agentic workflows and relevant frameworks, such as LangChain, LangGraph, Auto-GPT etc.
- Familiarity in AWS Cloud services such as EMR, Sagemaker etc.,
- Strong people management, team-building skills and ability to coach and grow talent, foster a healthy engineering culture and attract/retain talent, 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.

Preferred 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.
- Experience working at code level

---