Harnham
Senior MLOps Engineer 201043

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Senior MLOps Engineer
London (Hybrid) | Salary: up to £85,000
This is an opportunity to join a growing AI and data organisation where your work will directly support the deployment, scalability, and reliability of innovative machine learning solutions. You will play a pivotal role in building the infrastructure that enables advanced AI services to deliver real-world impact at scale.
The Company
They are a mission-led technology organisation that uses data, machine learning, and AI to help organisations make better decisions and deliver meaningful outcomes. With a growing client base and continued investment in their platform, they are expanding their engineering capabilities to support the next stage of growth. Their environment combines technical excellence with a strong focus on responsible AI, innovation, and continuous improvement. You will be joining a collaborative team where your expertise will help shape both the platform and the wider AI strategy.
The Role
- Build, maintain, and evolve the cloud infrastructure that supports machine learning and AI services in production.
- Deploy, manage, and monitor machine learning models using Azure ML, Azure Kubernetes Service (AKS), and related Azure services.
- Design and develop robust orchestration pipelines for model training, deployment, inference, and retraining workflows.
- Implement infrastructure-as-code solutions using tools such as Terraform, Bicep, or similar technologies.
- Establish monitoring, logging, alerting, and observability frameworks to ensure reliability and performance.
- Support scalable deployment across multiple client environments while maintaining security and operational excellence.
- Collaborate with data scientists, engineers, and wider business stakeholders to enable successful AI delivery.
- Contribute to AI governance, best practices, and responsible AI principles across the organisation.
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.
Start with a chat, not a search bar
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.
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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.
Your Skills & Experience
- Strong commercial experience within MLOps, Platform Engineering, or Infrastructure Engineering supporting machine learning systems.
- Advanced Python programming skills with a strong software engineering mindset.
- Hands-on experience with Azure-native MLOps services, including model deployment, pipelines, environments, and compute resources.
- Proven expertise deploying and managing containerised applications on Kubernetes.
- Experience building and maintaining CI/CD pipelines using Azure DevOps or similar tools.
- Knowledge of infrastructure-as-code approaches using Terraform, Bicep, Pulumi, or equivalent technologies.
- Experience implementing monitoring and observability solutions using tools such as Prometheus, Grafana, or similar.
- Familiarity with orchestration platforms including Dagster, Airflow, Prefect, or related technologies.


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Desirable experience includes:
- Model serving infrastructure for real-time or batch inference workloads.
- Multi-tenant platform environments.
- Vector databases such as Qdrant.
- Development of high-performance APIs and data-intensive services.
- Broader Azure ecosystem expertise including Azure Container Registry, Azure Blob Storage, Azure Monitor, and Azure Key Vault.
What They Offer
- The opportunity to work on innovative AI and machine learning projects with genuine societal impact.
How to Apply
If you are an experienced Senior MLOps Engineer looking to build scalable AI infrastructure in a collaborative and purpose-driven environment, apply today to discuss the opportunity in more detail.
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