Sainsbury's
ML / AI Platform Engineer

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Why join us
At Sainsbury's, we're investing in shared AI and machine learning platforms that enable teams across the business to build, deploy and operate intelligent solutions safely, securely and at scale.
You'll help shape the engineering foundations that power machine learning, generative AI and agentic applications across the organisation. Working as part of a platform engineering team, you'll build reusable capabilities that make it easier for product teams, data scientists and engineers to deliver value while meeting our standards for security, reliability, governance and cost efficiency.
Our platforms include:
- Azure Machine Learning
- AI Gateway capabilities built on Azure API Management
- Shared patterns and tooling for agentic and generative AI solutions
- Core platform services covering identity, networking, observability, security, deployment and cost management
You don't need to be an AI or machine learning specialist. We're looking for strong engineers with cloud platform, infrastructure or DevOps experience who are excited to apply their skills to the next generation of AI-enabled products and services.
What you'll do
- Design, build and operate shared platform capabilities that enable teams to develop and deploy ML and AI solutions efficiently and securely
- Create reusable infrastructure, tooling and automation that improves the developer experience and reduces operational overhead
- Build and maintain cloud-native platform services covering deployment, networking, security, identity, monitoring and governance
- Collaborate with product teams, data scientists and ML/AI Ops engineers to understand requirements and provide scalable platform solutions
- Drive engineering excellence through automation, standardisation, observability and reliability practices
- Contribute to the evolution of our AI and ML platform strategy, ensuring solutions remain secure, resilient and cost-effective
- Troubleshoot complex technical issues across cloud services, infrastructure and applications
- Support and mentor engineers within the team, sharing knowledge and driving continuous improvement
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Who you are
Essential skills and experience
- Experience building, operating or improving cloud platforms in AWS, Azure or GCP
- Strong understanding of infrastructure as code
- Strong programming skills, with experience developing production-quality solutions in Python or other modern programming languages
- Experience with CI/CD pipelines, Git-based workflows and modern software delivery practices
- Knowledge of cloud networking, identity management, security and access controls
- Experience managing containerised workloads and cloud-hosted application platforms
- Strong troubleshooting and problem-solving skills across infrastructure and application layers
- Experience building reusable platform capabilities and self-service engineering solutions
- Ability to lead technical initiatives and take ownership of delivery outcomes
- Strong collaboration and communication skills, with a willingness to coach and support others
- A growth mindset, with the ability to learn new technologies and apply sound engineering principles in unfamiliar domains


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Desirable skills and experience
- Experience with Microsoft Azure platform services
- Azure Machine Learning
- Azure API Management
- Azure OpenAI, Azure AI Foundry or related AI platforms
- Platform Engineering and Developer Experience practices
- MLOps, model deployment and model lifecycle management
- Experience operating platforms in large-scale enterprise environments
- Knowledge of generative AI architectures, AI gateways, agent frameworks or agentic delivery patterns
What success looks like
- Engineers can quickly and safely build and deploy ML and AI solutions using shared platform capabilities
- Platform services are secure, reliable, observable and cost-effective
- Reusable patterns and automation reduce duplication across teams
- Platform adoption grows through a great developer experience and strong engineering partnerships
- AI and ML workloads can be operated confidently at enterprise scale
Benefits
- Generous colleague discount across Sainsbury’s, Argos, and Habitat
- Competitive holiday allowance
- Bonus scheme
- Pension plan
- Flexible / smarter working policy
- Access to special offers on gyms, restaurants, holidays, retail vouchers and more
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