Bring your expertise to accelerate AI/ML strategic programs across the firm, 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 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

Formal training or certification on computer science, data science, information systems, electrical engineering concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise 10 + yrs of solid grasp of core algorithms, deep neural networks, and LLMs/SLMs with hands on experience with data/feature engineering, training, orchestration, model deployment/serving, model monitoring, and governance utilizing modern ML frameworks, libraries, and tools Bachelor’s degree in computer science, data science, information systems, electrical engineering, or equivalent experience Advanced knowledge of architecture, design, and software engineering processes Deep understanding and hands-on experience with public cloud technologies, especially with AWS and Azure, and DevOps processes and tools such as Containers, IaC, CI/CD, etc. Strong working experience with big data, data lakes/data mesh/lake house architectures, and ML data engineering processes, tools & techniques Keep abreast of advancements in technology and industry trends in the AI/ML space to be able to leverage the right stack for any given problem Collaborate with product management, platform engineering, security, risk management, and other partner organizations in discovery and requirements definition Leverage agile practices in continuously improving our delivery quality and velocity Work in large, collaborative teams to achieve organizational goals