We're looking for a Senior MLOps Engineer to lead the design, deployment, and support of Machine Learning platforms. This role will be key in defining the ML and AI strategy, delivering AI capabilities, and managing high-quality platforms. The ideal candidate will have proven experience in Machine Learning and MLOps, with expertise in various frameworks, technology, and DevOps tools.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
MLOps Engineer - KubeFlow - £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.
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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
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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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