Applied AI & ML Lead – Markets Operations

JPMorgan Chase JPMorgan Chase · Banking · LONDON, LONDON, United Kingdom · Commercial & Investment Bank

Lead the design, development, and delivery of AI/ML solutions for Market Operations at JPMorgan Chase, focusing on enhancing operations and scaling AI-driven tools. This role involves leading a team, partnering with stakeholders, and ensuring production-grade applications with robust architecture, evaluation, and governance.

What you'd actually do

  1. Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives.
  2. Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs.
  3. Mentor and guide a team of AI/ML data scientists, supporting iterative experimentation and tracking progress in an agile environment.
  4. Ensure production-grade AI/ML applications and tools are built, maintained, and optimized.
  5. Establish best practices for designing robust architectures, evaluation, monitoring, governance, and deployment.

Skills

Required

  • MSc or PhD in Computer Science, Data Science, Machine Learning, or related field.
  • Proven experience building and deploying AI applications in large-scale production environments.
  • Experience with MLOps practices and tools for managing the machine learning lifecycle.
  • Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.
  • Strong understanding of data preprocessing, feature engineering, and evaluation techniques.
  • Experience working with large, complex datasets and applying statistical analysis.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
  • Experience managing data science teams and coaching team members.
  • Problem-solving skills and ability to work independently and as a leader within cross-functional teams.
  • Strong communication skills for both technical and non-technical audiences.

Nice to have

  • Familiarity with prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites.
  • Hands-on experience with agentic frameworks (LangChain, LangGraph).
  • Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration.
  • Demonstrated experience in financial services, particularly investment banking operations.

What the JD emphasized

  • building and deploying AI applications in large-scale production environments
  • MLOps practices
  • managing data science teams

Other signals

  • leading a team
  • design and delivery of AI/ML solutions
  • enhance and transform Market Operations
  • implementation and scaling of AI-driven tools
  • identify opportunities
  • set technical direction
  • deliver measurable impact
  • foster a culture of collaboration and continuous learning
  • end-to-end delivery of advanced machine learning models
  • production-grade AI/ML applications
  • best practices for designing robust architectures, evaluation, monitoring, governance, and deployment
  • knowledge sharing
  • prioritizing development prerequisites
  • address and solve complex problems using AI/ML