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JPMorgan Director Architecture - Principal AI/ML Solutions Architect 
United States, New Jersey, Jersey City 
458617183

26.06.2024

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