Lead - Applied Artificial Intelligence and Machine Learning

Applied AI ML Lead

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

As an Applied AI ML Lead at JPMorganChase within Asset and Wealth Management, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

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.
• Creates 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.
• Adds to team 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 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. Advanced Python is a must.
• Robust understanding on design patterns, data structures & algorithms, software architecture & CI/CD pipeline in any cloud platform
• Solid 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 method 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 player
• Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.

• Experience with Ray, MLFlow, and/or other distributed training frameworks and experience in GPU optimization
• Advanced knowledge in Reinforcement Learning or Meta Learning.
• Open to learning and growth mindset