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🤖ML Engineer

Software Engineer III

JPMorgan Cha · GLASGOW, LANARKSHIRE, United Kingdom
// classified as
ML Engineer (Productionizing models, serving, MLOps.)
posted
1d ago
location
GLASGOW, LANARKSHIRE, United Kingdom
languages
—
tools
aws, azure, grafana
> stack
awsazuregrafanakubernetesterraform
> description

Are you passionate about building resilient, scalable systems that power the future of AI? At JPMorganChase, we're pushing the boundaries of what's possible with artificial intelligence and machine learning — and we need engineers like you to help us do it reliably, securely, and at scale.

As a Software Engineer III at JPMorganChase within the AI/ML Data Platforms organization, you will be a key member of the Reliability Engineering team, contributing to the design and delivery of trusted, market-leading technology products. You will apply your technical expertise and problem-solving skills to enhance the reliability and scalability of AI/ML platforms, build reusable services and tooling, and partner across teams to unblock high-impact AI use cases. This is an opportunity to shape how the firm delivers AI capabilities — with operational excellence at the core.

Responsibilities: 

  • Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast-growing demands.
  • Own NFRs and develop tooling for observability, security, resilience, infrastructure management and operations excellence.
  • Build and maintain scalable infrastructure to support the deployment and operation of large-scale AI platforms and apps.
  • Build strong cross-functional relationships that foster engagements across the organization and deliver solutions to user problems.
  • Participates in on-call rotations and escalation workflows, Debug and solve issues in a production environment, take full ownership of problems, develop solutions.
  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
  • Adds to team culture of diversity, opportunity, inclusion, and respect
     

Required qualifications, capabilities, and skills 

  • Formal training or certification on software engineering concepts and proficient applied experience.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced proficiency in programming with Python. 
  • Proficiency in all aspects of the Software Development Life Cycle.
  • Experience with infrastructure-as-code and cloud-native delivery practices, including tools such as Terraform, containers, Kubernetes, CI/CD pipelines, and automated deployment workflows.
  • Experience in designing and developing large-scale distributed systems and cloud-native architecture.
  • Experience building large scale infrastructure and and cloud-native delivery practice in Google Cloud, AWS, or Azure and Terraform. 
  • Extensive experience implementing advanced observability using tools like Open Telemetry, Dynatrace, Grafana, and/or cloud-native services.
  • Systematic problem-solving and troubleshooting skills in a complex system.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
     

Preferred qualifications, capabilities, and skills

  • Prior experience working in AI Cloud Infrastructure.
  • Prior experience developing GenAI Apps or AI Agents.
  • Previous experience as an Infrastructure or Platform Software Engineer in a dynamic technology company or startup.
  • Self-managed, self-motivated with strong sense of ownership, urgency, and drive
Apply at JPMorgan Cha →