Applied AI ML Engineer

JPMorgan Chase JPMorgan Chase · Banking · BOURNEMOUTH, DORSET, United Kingdom · Corporate Sector

This role focuses on helping customers build, deploy, and operate AI/ML models and agentic systems, with a strong emphasis on observability, large-scale data processing, secure deployment, and using coding assistants. The primary artifact is the agentic system (L4), with a secondary focus on the underlying inference infrastructure (L3).

What you'd actually do

  1. Assist customers in building and deploying models and agents across multiple model/agent frameworks (selection, integration patterns, troubleshooting, best practices).
  2. Implement and operate AI/ML observability: experimentation management, tracing, and monitoring to improve quality and reliability of model/agent behavior.
  3. Build and optimize large-scale data processing pipelines and feature workflows using distributed compute (e.g., Ray, Spark, or similar).
  4. Develop AI/ML systems using coding assistants to improve engineering efficiency while maintaining code quality standards.
  5. Ensure secure deployment and access for AI/ML services (e.g., secure-by-design practices, access controls, and environment separation), aligned to firm guidance for safe/responsible AI use.

Skills

Required

  • Hands-on experience supporting customers/teams delivering AI/ML products (model + agent workflows).
  • Experience with observability, evaluation/experimentation, and tracing platforms for AI/ML or LLM/agent systems.
  • Experience with distributed data processing at scale (Ray, Spark, or similar).
  • Strong software engineering skills (clean code, testing, CI/CD concepts, API/service development).
  • Strong communication skills and ability to translate requirements into practical engineering outcomes.

Nice to have

  • Experience integrating AI/ML into production systems (monitoring, incident response, change management).
  • Familiarity with responsible AI/ML governance expectations and lifecycle controls

What the JD emphasized

  • AI/ML models and agentic systems
  • AI/ML observability
  • large-scale data processing
  • coding assistants
  • secure deployment and access for AI/ML services
  • observability, evaluation/experimentation, and tracing platforms for AI/ML or LLM/agent systems

Other signals

  • AI/ML models and agentic systems
  • AI/ML observability
  • large-scale data processing
  • coding assistants
  • secure deployment and access for AI/ML services