Skills

Python Go Incident Response GitHub CI/CD Docker Kubernetes Monitoring Research Training Machine Learning Programming AWS Terraform Prometheus Grafana GitHub Actions

Job Specifications

Senior Machine Learning Operations Engineer - London (2x a week onsite) - PS500 p/d (Outside IR35) - 6-months Contract

We are seeking an experienced MLOps Engineer to join a globally known consumer tech company focused on building innovative, large-scale platforms. In this role, you will evolve and scale the machine learning platform, ensuring it supports high-throughput model inference and fast iteration cycles. This position is perfect for someone who thrives at the intersection of MLOps, Kubernetes, and cloud infrastructure, with a hands-on approach to solving complex challenges.

You will work closely with ML engineers and product teams to align infrastructure with evolving project needs, research and implement cutting-edge MLOps practices, and mentor colleagues by sharing expertise in cloud operations and ML engineering best practices.

The right candidate will also be responsible for managing GPU-powered Kubernetes clusters, improving automation pipelines, and ensuring system reliability. Candidates should have experience building and managing Kubernetes clusters from scratch, configuring them manually using tools like kubeadm, and deploying applications with Helm--demonstrating true infrastructure-level expertise rather than just deploying services on managed platforms.

Key Skills

MLOps & Kubernetes: GPU-enabled cluster management, built from scratch using kubeadm and Helm.
Programming: Python or Go for ML automation workflows.
Containerization: Docker and containerized application deployment.
Cloud: AWS experience supporting ML workloads.
CI/CD & Automation: ArgoCD, GitHub Actions, Infrastructure-as-Code (Terraform).
Monitoring & Observability: Prometheus, Grafana, cloud-native stacks.
ML Lifecycle: Production experience with experimentation, training, deployment, versioning, and monitoring.
Reliability & Support: On-call participation, incident response, and system optimization.

The ideal candidate will be a Senior MLOps Engineer with extensive, hands-on experience in Kubernetes, ready to make an impact at a globally recognised consumer tech company

Location: London (2x a week onsite)

Day rate: PS500 p/d (Outside IR35)

Duration: 6-month

About the Company

Ventula Consulting is a boutique recruitment firm determined to see our clients grow through hiring exceptional people. Ventula was formed in July 2013 to provide the next generation of recruitment services. We utilize the latest techniques in digital talent attraction and are experts at proactively promoting our clients brands and mission statements to help them attract the highest calibre candidates in an increasingly competitive market. The recruitment landscape has changed dramatically over recent years. Ventula’s evolu... Know more