Staff Machine Learning Engineer - Ops (MLOps)

Location: Hybrid role based in the London office, combining office and home working

Company

hirify.global develops embodied AI software and foundation models for mapless, hardware-agnostic automated driving systems.

What you will do

• Define and enforce release gates across the multi-phase ML training lifecycle.
• Review model changes, metric changes, and evaluation results against quality and safety standards before release.
• Identify ML delivery bottlenecks and drive improvements that increase speed without compromising quality.
• Define and build checks and automation with AI Platform teams to detect issues earlier.
• Adapt CI/CD workflows and streamline model delivery in collaboration with CI/CD teams.
• Improve evaluation methods by identifying gaps and developing new methodologies.

Requirements

• Experience introducing operational processes that improve engineering excellence.
• Strong experience with MLOps, model registries, and the ML lifecycle.
• Deep technical understanding of ML training and ML code infrastructure best practices.
• Experience with PyTorch, TensorRT, quantisation, and model deployment.
• Strong CI/CD and GitHub Actions experience.
• Strong communication skills and a collaborative mindset.

Nice to have

• Experience with Grafana monitoring and production observability.

Culture & Benefits

• Hybrid working with time in offices and workshops alongside time working from home.
• Inclusive and respectful working environment that values diverse perspectives.
• Interview accommodations and adjustments are available when required.