JPMorgan Director Architecture - Principal AI/ML Solutions Architect 

United States, New Jersey, Jersey City 

458617183

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