Machine Learning Operations Engineer (SaaS)

Oliver Bernard United Kingdom
Remote
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AI Summary

Oliver Bernard is seeking a Machine Learning Operations Engineer to build and support machine learning platforms for their SaaS solutions. You'll work in their Data Platforms team, designing and deploying scalable platforms for running production machine learning software. A successful candidate will have experience in machine learning frameworks, DevOps, and MLOps.

Key Highlights
Design and deploy machine learning platforms
Support platform deployments and CI/CD tools
Work in the Data Platforms team
Key Responsibilities
Design and build high-quality, scalable platforms for running production machine learning software
Help define the overall strategy and roadmap for ML and AI
Support platform deployments and CI/CD tools and processes
Technical Skills Required
Cloud (AWS, Azure, GCP, OpenStack) DevOps (Kubernetes, Observability, IaC, CI/CD) Machine learning frameworks (Python, Spark, MLlib, Tensorflow, PyTorn) Linux REST FastAPI
Benefits & Perks
£75K - £100K salary
Fully remote working
Nice to Have
Good knowledge of Security

Job Description


MLOps Engineer - SaaS - £75K - £100K


Our client is a leading software as a service (SaaS) company, building cutting-edge solutions for trading, egaming and payments all over the world.


Offering fully remote working, they’re looking to hire an MLOps Engineer.


You’ll work in their Data Platforms team and be key in the design, building and support of Machine Learning platforms to deliver the power and scale of AI capabilities.


Work will include the design and deployment of high quality, scalable platforms for running production Machine Learning software, helping define the overall strategy and roadmap for ML and AI and supporting platform deployments and CI/CD tools and processes.


You’ll need a positive, growth, mindset, great experience of ML frameworks and software delivery and good knowledge of DevOps, MLOps and Security.


Requirements:


  • Proven Machine Learning and MLOps experience
  • Good knowledge of Cloud - AWS, Azure, GCP, OpenStack etc
  • Solid DevOps experience - Kubernetes, Observability, IaC, CI/CD etc
  • Coding skills using Python, Ruby, Perl etc
  • Strong understanding of software development, modern tech and frameworks
  • Solid Linux knowledge


Tech / Tools you’ll be working with (some of them!)


  • Kubeflow
  • Spark / MLlib / Tensorflow / PyTorn
  • REST / FastAPI
  • Docker / Kubernetes
  • Terraform / Ansible
  • GitOps
  • Python / Bash

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