Senior Software Engineer - MLOps

AIOI R&D Lab - Oxford; Oxford; Hybrid; GBP 65,000 - 90,000; Full time

Job summary

Aioi R&D Lab – Oxford is seeking a hands-on infrastructure engineer to build the cloud platforms and ML tooling underpinning our research programs.

You will design and operate secure cloud infrastructure, model hosting, training pipelines, and agentic development tooling, with room to grow seniority.

Qualifications

• 5+ years of commercial software engineering experience.
• Strong Python with ML data libraries.
• Experience deploying cloud services and managing storage.

Responsibilities

• Design, build, and run cloud infrastructure for CODAS.
• Build model hosting and training infrastructure, secure data storage, and agentic tooling.
• Write clean, well-tested code and contribute to CI/CD and docs.
• Support integration with partner environments and research workflows.
• Explain trade-offs and learn fast as requirements evolve.

Skills

Python

Cloud infra

Kubernetes

CI/CD

ML libraries (pandas, numpy, scikit-le

Testing & packaging

Team collaboration

Tools

AWS

Git

Helm

Kubectl

Terraform

Job description

Aioi R&D Lab – Oxford is an AI R&D company based in Oxford, on a mission to harness AI to understand, predict, and manage risk, helping build a safer, more resilient society.

We sit at the intersection of academia and industry, working with Oxford's professors, researchers, and graduates alongside commercial spinouts and partner companies, to turn frontier research into AI that actually ships rather than just gets published.

Our work spans applied AI for insurance and adjacent industries, including supply chains, nature, autonomous driving, and the emerging challenges nobody's solved yet, alongside deep research of our own into agentic AI, privacy-preserving technologies, trustworthy AI, complex systems modelling, and quantum computing.

We build AI products and solutions for insurers, businesses, and public-sector organisations worldwide, and run innovative research projects that push these technologies further, helping people make better decisions in an uncertain world.

Contract:

18-month fixed-term contract from signing (running to at least January 2028), with a view to extending or moving to permanent as a second round of programme funding is confirmed

Location:

Oxford, hybrid preferred, though we'd consider fully remote for the right person

The role

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.

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.

What you'll do

• 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.

What you'll bring

• 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.

Bonus points:

LLM serving/fine‑tuning (even personal projects), agentic AI frameworks (LangGraph, AutoGen, CrewAI), Kubeflow/KServe, GitOps/IaC (Flux, Terraform), or an interest in privacy‑preserving techniques.

• A genuinely hands‑on infrastructure role on a high‑profile sovereign AI programme, not a ticket queue.
• Room to grow: the stack isn't fully fixed, so there's real scope to shape it and grow your seniority alongside the programme.
• Work directly with Oxford's research network and an ambitious international partner group, not several layers removed from the interesting problems.
• This is a fixed‑term contract tied to CODAS's current funding cycle, but there's a genuine intent to extend and move roles to permanent as a second funding round is confirmed. It isn't a contract designed to end.