Tech Stack

Description

Build and evolve the platform that takes ML models from research to reliable, scalable production. Work at the intersection of ML, infrastructure, and software engineering, partnering with ML engineers to improve performance, reliability, and cost efficiency.

Requirements

• Python skills for production systems
• Experience optimising model training and inference, including GPU-based and distributed workloads
• Experience with containerisation and orchestration (Docker, Kubernetes)
• Strong background in monitoring, observability, and reliability for ML platforms

Responsibilities

• Design, build, and maintain scalable ML platforms, tools, and infrastructure
• Migrate ML workloads from SGE Grid Engine to Kubernetes-based orchestration (Slurm/Ray)
• Optimise ML infrastructure for GPU utilisation and distributed training
• Build and maintain CI/CD workflows for ML systems
• Evaluate new tools and frameworks to improve ML platform efficiency and reliability