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Lead Software Engineer

JPMorganChase

Salary not specified
Sep 6, 2025
McLean, VA, US
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JPMorgan Chase is looking to build, launch and scale an AI/ML platform for the firm, integrating cutting-edge technologies like Generative AI, and needs a Lead Software/ML Engineer to shape the future of AI/ML at the company.

Requirements

  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • Extensive hands-on experience with ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn, Ray or Spark).
  • Extensive experience with a Public Cloud provider (AWS, Azure, GCP) and addressing non-functional requirements such as scalability and cross-region resiliency.
  • Strong coding skills and experience in developing large-scale ML systems and ensuring Software Best Practices.
  • Experience with prompt engineering and interacting with various LLM vendors and models.
  • Proven track record in contributing to and optimizing open-source ML frameworks.
  • Expertise in Kubernetes ecosystem, including EKS, Helm, and custom operators.

Responsibilities

  • Architects and implements distributed ML infrastructure, including inference, training, scheduling, orchestration, and storage.
  • Develops advanced monitoring and management tools for high reliability and scalability.
  • Optimizes system performance by identifying and resolving inefficiencies and bottlenecks.
  • Collaborates with product teams to deliver tailored, technology-driven solutions.
  • Drives the adoption and execution of ML Platform tools across various teams.
  • Integrates Generative AI within the ML Platform using state-of-the-art techniques.
  • Coordinates the inference needs of JPMorgan Chase’s research teams, ensuring alignment with business goals.

Other

  • 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.
  • Formal training or certification on software engineering concepts
  • 5+ years applied experience