Senior Software Engineer (MLOps) - 18 month FTC, Aioi R&D Lab

• 5+ years of commercial software experience, with a track record of shipping maintainable code in a team
• Solid Python, including the core data/ML libraries (pandas, numpy, scikit-learn) and good instincts on structure, testing, and packaging
• Practical cloud infrastructure experience, including deploying services, managing storage, and working with access controls. AWS preferred, but strong experience with another provider counts
• Familiarity with Kubernetes and Helm, and comfort with CI/CD, version control, and containerisation as everyday tools
• Some exposure to ML infrastructure or data engineering, such as training pipelines, model serving, experiment tracking, or data pipelines
• The ability to explain what you've built, why, and what trade-offs you made

Desirable

• You'd join a small, technically strong engineering team, led by an experienced Technical Lead, building the infrastructure that CODAS runs on: secure cloud infrastructure, ML model serving and training pipelines, and agentic development tooling. This is a hands-on infrastructure and platform role with genuine room to grow into more senior technical responsibility as the programme scales
• Help design, build, and run the cloud infrastructure behind a privacy-preserving AI research programme, working under the Technical Lead
• Build model hosting and training infrastructure, secure data storage, and agentic development tooling that the research tracks depend on
• Write clean, well-tested, maintainable code, and contribute to shared engineering standards, CI/CD, and documentation
• Support integration with partner environments and research workflows, troubleshooting issues as they come up
• Get stuck into technical trade-offs, ask good questions, and learn fast as tools and requirements evolve
• We're not expecting you to already have deep experience across every part of this stack. We're looking for a strong engineer with solid fundamentals, who picks up new tools fast and cares about building things that work reliably and responsibly