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Senior MLOps Engineer

La Fosse United Kingdom
Remote
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AI Summary

Partner with a well-known organisation to build and scale its next-generation ML platform. Design, deploy, and maintain machine learning services across a modern cloud environment. Contribute to infrastructure automation and drive improvements in platform performance and maintainability.

Key Highlights
Design, build and maintain infrastructure for deploying machine learning models into production
Develop and maintain Python APIs using FastAPI and/or Flask
Work closely with Data Scientists to productionise models and improve deployment reliability
Key Responsibilities
Design, build and maintain infrastructure for deploying machine learning models into production
Develop and maintain Python APIs using FastAPI and/or Flask
Work closely with Data Scientists to productionise models and improve deployment reliability
Build and enhance CI/CD pipelines for machine learning deployment workflows
Implement monitoring, observability, and model lifecycle management processes
Build scalable cloud-native solutions using modern engineering best practices
Contribute to infrastructure automation through Infrastructure as Code
Drive improvements in platform performance, resilience, security, and maintainability
Technical Skills Required
Python FastAPI GCP
Benefits & Perks
£475-500/day
Remote in the UK
Initial 6 Months Contract

Job Description


Senior MLOps Engineer | Contract Role


Outside IR35 | £475-500/day | Remote in the UK | Initial 6 Months


We're partnering with a well-known organisation that is investing heavily in its machine learning capability and looking for a Senior MLOps Engineer to help build and scale its next-generation ML platform.


This is a highly hands-on role focused on productionising machine learning solutions, building deployment pipelines, and developing the infrastructure that enables Data Science teams to deliver models reliably at scale.


You'll work closely with Data Scientists, Platform Engineers, and Software Engineers to design, deploy, monitor, and maintain machine learning services across a modern cloud environment.

This is a fantastic opportunity to join a growing function where you'll have significant influence over platform design, engineering standards, and the future direction of MLOps within the business.


Outside IR35, fully remote, with an initial 6-month contract and strong potential for extension.


Key Responsibilities

  • Design, build and maintain infrastructure for deploying machine learning models into production
  • Develop and maintain Python APIs using FastAPI and/or Flask
  • Build and enhance CI/CD pipelines for machine learning deployment workflows
  • Implement monitoring, observability, and model lifecycle management processes
  • Work closely with Data Scientists to productionise models and improve deployment reliability
  • Build scalable cloud-native solutions using modern engineering best practices
  • Contribute to infrastructure automation through Infrastructure as Code
  • Drive improvements in platform performance, resilience, security, and maintainability


Ideal Candidate

  • Strong experience as an MLOps Engineer
  • Proven experience deploying and maintaining machine learning models in production environments
  • Strong software engineering fundamentals with Python development experience
  • Experience building APIs and production-grade backend services
  • Comfortable working closely with Data Scientists and translating research into production systems
  • Experience operating within Agile development environments
  • Strong problem-solving skills and ability to work independently on complex technical challenges


Tech Stack Required:

  • Python
  • GCP (Vertex AI preferred)
  • FastAPI or Flask
  • Terraform
  • Docker
  • CI/CD Pipelines
  • Git
  • Infrastructure as Code


If you are interested please apply below!


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