Ml Ops Engineer

CMC MARKETS

London, United Kingdom
Ml lifecycle infrastructure
Productionizing models
Ci/cd pipelines for ml
This role sits at the intersection of data engineering and ML infrastructure, designing and operating data pipelines and building tooling for ML model lifecycle management

Job Summary

  • This role sits at the intersection of data engineering and ML infrastructure, designing and operating data pipelines and building tooling for ML model lifecycle management.
  • You will be responsible for the reliability, scalability, and operational integrity of machine-learning systems in research and production, taking models from experimentation to production-grade systems with clear SLAs.
  • This is a hands-on engineering role focused on making ML systems work reliably at scale, reducing the gap between promising experiments and systems that can be trusted by downstream products and customers.

Matching Summary

This role sits at the intersection of data engineering and ML infrastructure, designing and operating data pipelines and building tooling for ML model lifecycle management.

Skills & Requirements

Must-have

  • ML lifecycle infrastructure
  • productionizing models
  • CI/CD pipelines for ML
  • model monitoring
  • experiment tracking
  • data pipelines
  • operational ownership
  • production-grade Python

Nice-to-have

  • TB-scale data volumes
  • automated retraining
  • feature stores
  • shared ML platform
  • regulated environments

Key Requirements

  • 3-7 years of professional experience
  • Strong production Python skills
  • Experience deploying and operating ML models
  • Solid understanding of ML training vs. inference
  • Hands-on experience with orchestration systems
  • Comfort with cloud infrastructure and containers

Work Rights

Not specified

Tailored Resume

Cover Letter