The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the adoption of advanced AI/ML technologies across the firm. Bring your expertise to take part in this exciting mission, utilizing your strong and insightful technical and people skills. We look, first and foremost, for people who are passionate about solving business problems through informed strategic vision, creative innovation, and modern ML architecture & engineering practices, leveraging our purpose-built Machine Learning platforms and/or commercial AI/ML platforms and related technologies.

As a Director of Architecture at JPMorgan Chase within the AI/ML Solution Architecture Group, you will be presented with numerous opportunities to utilize your extensive knowledge and expertise across all aspects of the machine learning lifecycle. Our work environment promotes collaboration, trust, and thought-provoking discussions, fostering diversity of thought and innovative solutions that serve the best interests of our global customers.

Job Responsibilities

• Engage with business stakeholders to refine requirements, assist with framing business problems as machine learning problems, and help define success metrics
• Define appropriate data engineering processes to facilitate data preparation and feature engineering
• Collaborate with data scientists and data and ML engineers in selecting and evaluating ML models and algorithms using factors such as accuracy, scalability, interpretability, etc.
• Develop end-to-end AI/ML solutions in compliance with and leveraging firm’s policies, standards, and AI/ML governance processes
• Provide technical leadership throughout the entire machine learning lifecycle, in collaboration with architecture, security, risk, operations, and other partner organizations
• Design and lead proof-of-concepts, commercial product evaluations, and custom solutions

Required qualifications, capabilities, and skills

• Bachelor’s degree or higher in computer science, data science, information systems, or electrical engineering and 10+ years of applied experience in software architecture and machine learning systems.
• Experience with core machine learning algorithms, deep neural networks, NLP, and LLMs/SLMs.
• Advanced knowledge of software architecture and development for machine learning systems with hands on experience throughout the entire machine learning lifecycle.
• Deep understanding and hands-on experience with public cloud technologies, especially with AWS & its machine learning stack (Azure OpenAI experience would be a strong plus).
• Working experience with big data, data lakes/data mesh/lake house architectures, and ML data engineering processes, tools & techniques.
• Significant experience with one or more programming languages, at least Python and Java, and DevOps processes and tools such as Containers, Iac, CI/CD, etc.