Applied AI & ML Lead – Markets Operations

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

Lead a team of AI/ML scientists and engineers to design, develop, and deploy AI/ML solutions for market operations in a large financial institution. Focus on end-to-end delivery, production deployment, MLOps, and stakeholder engagement.

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
  • agentic frameworks
  • prompt optimization frameworks

Other signals

  • lead the design and delivery of AI/ML solutions
  • lead a team of scientists and engineers
  • ensure the successful implementation and scaling of AI-driven tools
  • deliver measurable impact through innovative AI/ML applications