AI Platform Engineer — Kubernetes & GPU Infra (Hybrid)

Cubiq Recruitment; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Bonus

Equity

Job summary

Cubiq Recruitment is representing an early-stage AI research lab in London seeking a Platform/DevOps Engineer to design and build a scalable platform. You will own the Kubernetes estate, manage GPU scheduling, and develop infrastructure across GCP and other cloud providers. Strong Python skills and Rust experience are essential.

You’ll improve developer tooling, logging/monitoring, and create dashboards used by researchers to spot issues quickly. Hybrid work model offered.

Qualifications

• Kubernetes in production at scale
• Built and owned monitoring and logging for complex systems
• Strong cloud infra experience (GCP preferred)
• Production-quality Python code
• Rust experience
• Experience with Cody tooling
• Exposure to ML workloads and GPU scheduling
• Improved engineers’ tooling and local environments
• Platform/DevOps or infrastructure background in big tech or AI labs

Responsibilities

• Make core design decisions while the platform is being built
• Run and grow the Kubernetes estate and internal tooling
• Manage GPU workloads across a large cluster with schedulers like Kueue and KAI
• Investigate hardware failures and implement fixes to prevent recurrence
• Build and maintain infrastructure on GCP and other clouds
• Set up logging, metrics and dashboards used by engineers and researchers
• Improve developer environments and tooling to speed up research
• Write platform code primarily in Python, with Rust where fitting
• Take on roles where the research team needs core platform support

Skills

Kubernetes production

Monitoring & logging

Cloud infrastructure

Python

Rust

GPU scheduling

DevOps tooling

Platform experience

Research lab experience

Tools

Cody

Job description

Cubiq Recruitment is representing an early-stage AI research lab in London seeking a Platform/DevOps Engineer to design and build a scalable platform. You will own the Kubernetes estate, manage GPU scheduling, and develop infrastructure across GCP and other cloud providers. Strong Python skills and Rust experience are essential.

You’ll improve developer tooling, logging/monitoring, and create dashboards used by researchers to spot issues quickly. Hybrid work model offered.