We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Applied AI/ML Lead at JPMorgan Chase within the Asset and Wealth Management, you will provide deep engineering expertise and work across agile teams to enhance, build and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices and technological advances. This role will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions.

 

Job responsibilities

Establishes and promotes a library of common ML assets, including reusable ML models, features stores, data pipelines, and standardized templates.

Leads efforts to create shared tools and platforms that streamline the end-to-end ML lifecycle across the organization.

Creates curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques.

Gains Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines

Advises on the strategy and development of multiple products, applications, and technologies.

Leads advisor on the technical feasibility and business need for AIML use cases.

Liaises with firm wide AI ML stakeholders.

Translates highly complex technical issues, trends, and approaches leadership to drive the firm's innovation and enable leaders to make strategic, well informed decisions about technology advancements.

Influences across business, product and technology teams and successfully manages senior stakeholder relationships.

Champions the firm's culture of diversity, opportunity, inclusion, and respect.

 

Required qualifications, capabilities, and skills

Formal training or certification on Machine Learning concepts and 5+ years applied experience. MS and/or PhD in Computer Science, Machine Learning, or a related field and practical cloud native experience such as AWS needed.Experience in one of the programming languages like Python, Java, etc. Advance Python is a must.Robust understanding on design patterns, data structures, algorithms, software architecture and CI/ CD pipeline in any cloud platformSolid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs)Hands-on experience with machine learning and deep learning methods. Hands on code and design experience to bring the experimental results into production solutions by collaborating with engineering team. Experience in advanced applied ML areas such as fine-tuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search / Ranking).Passion for detail and follow through. Excellent communication skills and team playerDemonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.Open to learning and growth mindset 
 Preferred qualifications, capabilities, and skills

Experience with Ray, MLFlow, and/or other distributed training frameworks and experience in GPU Optimization. 

Advanced knowledge in Reinforcement Learning or Meta Learning.