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Applied AIML Director - GenAI

JP Morgan Chase

Salary not specified
Sep 17, 2025
Seattle, WA, USA
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The Corporate AI ML Technology Group is seeking a technical leader to shape the future of AI and ML solutions, specifically in the development of Agentic Systems within the firm.

Requirements

  • Extensive hands-on experience with ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn)
  • Deep expertise in AWS / GCP and Kubernetes ecosystem, including EKS, Helm, and custom operators
  • Strong coding skills and experience in developing large-scale ML systems
  • Background in High Performance Computing, ML Hardware Acceleration (e.g., GPU, TPU, RDMA), or ML for Systems
  • Proven track record in contributing to and optimizing open-source ML frameworks

Responsibilities

  • Define and drive the long term vision for agentic AI development: Includes strategic opportunities for agentic AI within the organization and setting the direction for research and development efforts.
  • Lead and manage a team of AI researchers and engineers: this involves hiring, mentoring, and providing technical guidance to the team.
  • Translate AI advancements into practical, scalable solutions: You will be responsible for taking research prototypes and turning them into robust, production-ready applications.
  • Oversee the development and deployment of agentic AI systems: This includes ensuring the quality, performance, and reliability of the AI Systems as well as their ethical and responsible development.
  • Collaborate with other teams and stakeholders: you will work closely with product management, engineering, and business teams to align AI initiatives with overall business objectives.

Other

  • 10+ years of experience in engineering management with a strong technical background
  • Strategic thinker with the ability to craft and drive a technical vision for maximum business impact
  • Demonstrated leadership in working effectively with engineers, data scientists, and ML practitioners
  • Proven ability to identify trade-offs, clarify project ambiguities, and drive decision-making