ML Platform Engineer

As a ML Platform Engineer, you will build and evolve the platform that takes our machine learning models from research to reliable, scalable production. Working at the intersection of machine learning, infrastructure, and software engineering, you will partner closely with ML engineers to improve performance, reliability, cost efficiency, and the overall maturity of our ML platform.

If you enjoy designing robust systems, automating complex workflows, and optimising ML platforms for performance, reliability, and cost, this role is for you.

What you will be doing

• Designing, building, and maintaining scalable ML platforms, tools, and infrastructure that enable teams to efficiently train, experiment with, and evaluate machine learning models
• Modernising the ML platform by migrating workloads from SGE Grid Engine to Kubernetes‑based orchestration systems such as Slurm or Ray, improving scalability, reliability, and efficiency of ML workflows.
• Modernising the ML workflows with cutting-edge tools for pipeline orchestration, experiment tracking, observability, and model versioning.
• Optimising ML infrastructure to maximise GPU utilisation, streamline scheduling, and enhance distributed training performance.
• Building and maintaining CI/CD workflows for ML systems, including model versioning, testing, and release automation.
• Collaborating closely with ML engineers to ensure models are deployable, reproducible, and production-ready.
• Continuously evaluating new tools, frameworks, and approaches to improve the efficiency, reliability, and maturity of the ML platform.
• Promoting operational excellence by reducing manual processes, improving automation, and raising the overall platform reliability and efficiency.
• Contributing to the ML platform roadmap, tooling standards, and best practices to support excellence in Voice AI.

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