Senior ML Engineer & AI Platform Lead

JP Morgan Chase

Greater London

On-site

GBP 62,000 - 102,000

Full time

13 days ago
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Job summary

JP Morgan Chase is seeking an experienced machine learning engineer to design and deliver enterprise-grade ML systems within a global financial services context. You will collaborate with cloud and SRE teams to build robust production architectures and translate scientific research into scalable ML solutions.

The role requires strong CS fundamentals, extensive AWS and Kubernetes experience, and proficiency with PyTorch and NumPy.

Qualifications

  • Experience in machine learning engineering roles.
  • Degree in a quantitative discipline (CS, Math, or Stats).
  • Proven ability to deploy business-critical, data-intensive apps.
  • Extensive AWS and Kubernetes experience.
  • Proficiency with PyTorch and NumPy.
  • Hands-on in distributed, multi-threaded, scalable apps.

Responsibilities

  • Design and deliver enterprise-grade ML systems.
  • Collaborate with cloud and SRE teams for robust production architectures.
  • Translate scientific research into scalable ML solutions.
  • Develop and deploy business-critical data-intensive applications.
  • Implement distributed, multi-threaded, scalable apps.
  • Build, test, and deploy automated ML pipelines.
  • Leverage libraries and services for reuse across teams.
  • Apply software engineering and CS best practices.
  • Utilize MLOps tools for versioning and observability.
  • Align ML problems with business objectives.
  • Mentor and support team members; potential for management.

Skills

Machine learning engineering
ML pipelines
Mentoring / leadership
Agentic AI concepts
CS fundamentals
MLOps tooling
Reusable libraries
Business alignment

Education

Degree in Computer Science, Mathematics, or Statistics

Tools

AWS
Kubernetes
PyTorch
NumPy

Job description

JP Morgan Chase is seeking an experienced machine learning engineer to design and deliver enterprise-grade ML systems within a global financial services context. You will collaborate with cloud and SRE teams to build robust production architectures and translate scientific research into scalable ML solutions.

The role requires strong CS fundamentals, extensive AWS and Kubernetes experience, and proficiency with PyTorch and NumPy.

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